Image processing system and method

ABSTRACT

A high-definition image is preprocessed to generate a substantially losslessly-reconstructable set of image components that include a relatively low-resolution base image and a plurality of extra-data images that provide for progressively substantially losslessly reconstructing the high-definition image from the base image, wherein a single primary-color component of the extra-data images provides for relatively quickly reconstructing full-resolution intermediate images during the substantially lossless-reconstruction process.

CROSS-REFERENCE TO RELATED APPLICATIONS

The instant application is a continuation-in-part of InternationalApplication No. PCT/US2019/031627 filed on 9 May 2019, with claimsdivided from International Application No. PCT/US2019/031627, the latterof which claims the benefit of prior U.S. Provisional Application Ser.No. 62/669,306 filed on 9 May 2018. The instant application also claimsthe benefit of prior U.S. Provisional Application Ser. No. 62/934,460filed on 12 Nov. 2019. Each of the above-identified applications isincorporated herein by reference in its entirety.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an image processing system that provides forpreprocessing a high-definition image to provide for a progressive,accelerated download from an internet server of components thereof in aform that provides for a progressive lossless reconstruction of thehigh-definition image on a client system;

FIG. 2 illustrates a process for progressively compacting ahigh-definition image using successive horizontal and verticalcompaction processes illustrated in FIGS. 3a-b and 4a-b , respectively,to form a corresponding reduced-resolution counterpart image and aplurality of associated extra-data images that, in combination with thereduced-resolution counterpart image, provide for losslesslyreconstructing the high-definition image;

FIG. 3a illustrates the equations of a process for horizontallycompacting a pair of vertically-adjacent image cells of a source image,so that the resulting compacted image has half the number of rows as thesource image when the process is applied to the entire source image, andso as to generate a corresponding extra-data image in one-to-one pixelcorrespondence with the resulting compacted image;

FIG. 3b illustrates the compaction of a pair of image pixels inaccordance with the horizontal-compaction process illustrated in FIG. 3a;

FIG. 4a illustrates the equations of a process for vertically compactinga pair of horizontally-adjacent image cells of a source image, so thatthe resulting compacted image has half the number of columns as thesource image when the process is applied to the entire source image, andso as to generate a corresponding extra-data image in one-to-one pixelcorrespondence with the resulting compacted image;

FIG. 4b illustrates the compaction of a pair of image pixels inaccordance with the vertical-compaction process illustrated in FIG. 4 a;

FIG. 5 illustrates a portion of a high-definition source imagecomprising M=16 rows and N=16 columns of image pixels, and theassociated image-pixel elements of four adjacent image pixels associatedwith a pair of adjacent rows, and a corresponding pair of adjacentcolumns, of the source image;

FIG. 6a illustrates a horizontal compaction of the high-definitionsource image illustrated in FIG. 5, in accordance with thehorizontal-compaction process illustrated in FIGS. 3a and 3 b;

FIG. 6b illustrates the extra-data image resulting from thehorizontal-compaction process as applied to the high-definition sourceimage illustrated in FIG. 5, to generate the horizontally-compactedimage illustrated in FIG. 6a , wherein the image-pixel elements of theextra-data image illustrated in FIG. 6b are in one-to-one correspondencewith those of the horizontally-compacted image illustrated in FIG. 6 a;

FIG. 7a illustrates a vertical compaction of the horizontally-compactedimage illustrated in FIG. 6a , in accordance with thevertical-compaction process illustrated in FIGS. 4a and 4 b;

FIG. 7b illustrates the extra-data image resulting from thevertical-compaction process as applied to the horizontally-compactedimage illustrated in FIG. 6a , to generate the vertically-compactedimage illustrated in FIG. 7a , wherein the image-pixel elements of theextra-data image illustrated in FIG. 7b are in one-to-one correspondencewith those of the vertically-compacted image illustrated in FIG. 7 a;

FIG. 8a illustrates the equations of a process for bidirectionallycompacting a quad of image cells from a pair of adjacent rows and a pairof adjacent columns of a source image, so that the resulting compactedimage has half the number of rows and half the number of columns as thesource image when the process is applied to the entire source image, andso as to generate a corresponding extra-data image that has threeextra-data pixel elements corresponding to each corresponding pixelelement in the resulting compacted image;

FIG. 8b illustrates the compaction of a quad of image pixels inaccordance with the process illustrated in FIG. 8 a;

FIG. 9a illustrates a bidirectional compaction of the high-definitionsource image illustrated in FIG. 5, in accordance with thebidirectional-compaction process illustrated in FIGS. 8a and 8 b;

FIG. 9b illustrates the extra-data image resulting from thebidirectional-compaction process as applied to the high-definitionsource image of illustrated in FIG. 5, to generate thebidirectionally-compacted image illustrated in FIG. 9a , wherein foreach pixel element in the bidirectionally-compacted image illustrated inFIG. 9a , there are three corresponding image-pixel elements in theextra-data image illustrated in FIG. 9 b;

FIG. 10a illustrates a horizontal compaction of thebidirectionally-compacted image illustrated in FIGS. 7a and 9a , inaccordance with the horizontal-compaction process illustrated in FIGS.3a and 3 b;

FIG. 10b illustrates the extra-data image resulting from thehorizontal-compaction process as applied to the high-definition sourceimage of illustrated in FIGS. 7a and 9a , to generate thehorizontally-compacted image illustrated in FIG. 10a , wherein theimage-pixel elements of the extra-data image illustrated in FIG. 10b arein one-to-one correspondence with those of the horizontally-compactedimage illustrated in FIG. 10 a;

FIG. 11a illustrates a vertical compaction of the horizontally-compactedimage illustrated in FIG. 10a , in accordance with thevertical-compaction process illustrated in FIGS. 4a and 4 b;

FIG. 11b illustrates the extra-data image resulting from thevertical-compaction process as applied to the horizontally-compactedimage illustrated in FIG. 10a , to generate the vertically-compactedimage illustrated in FIG. 11a , wherein the image-pixel elements of theextra-data image illustrated in FIG. 11b are in one-to-onecorrespondence with those of the vertically-compacted image illustratedin FIG. 11 a;

FIG. 12a illustrates the equations of a process for losslesslyvertically reconstructing a pair of horizontally-adjacent image cells ofa source image from a corresponding value of a corresponding image cellof a corresponding vertically-compacted image in combination with acorresponding value of a corresponding extra-data image cell of acorresponding extra-data image;

FIG. 12b illustrates a lossless vertical reconstruction of a pair ofhorizontally-adjacent image pixels in accordance with the losslessvertical-reconstruction process illustrated in FIG. 12 a;

FIG. 12c illustrates application of the lossless vertical reconstructionprocess illustrated in FIG. 12a , as applied to the Red (R), Green (G),Blue (B) and transparency (a) image-pixel elements of avertically-compacted image pixel to generate corresponding image-pixelelements of corresponding horizontally-adjacent image pixels of acorresponding source image;

FIG. 13a illustrates the equations of a process for losslesslyhorizontally reconstructing a pair of vertically-adjacent image cells ofa source image from a corresponding value of a corresponding image cellof a corresponding horizontally-compacted image in combination with acorresponding value of a corresponding extra-data image cell of acorresponding extra-data image;

FIG. 13b illustrates a lossless horizontal reconstruction of a pair ofvertically-adjacent image pixels in accordance with the losslesshorizontal-reconstruction process illustrated in FIG. 13 a;

FIG. 13c illustrates application of the lossless horizontalreconstruction process illustrated in FIG. 13a , as applied to the Red(R), Green (G), Blue (B) and transparency (a) image-pixel elements of ahorizontally-compacted image pixel to generate corresponding image-pixelelements of corresponding vertically-adjacent image pixels of acorresponding source image;

FIG. 14a illustrates the equations of a process for losslesslybidirectionally reconstructing a quad of image cells from a pair ofadjacent rows and a pair of adjacent columns of a source image, from acorresponding value of a corresponding image cell of a correspondingbidirectionally-compacted image in combination with corresponding valuesof corresponding extra-data image cells of a corresponding extra-dataimage;

FIG. 14b illustrates a lossless bidirectional reconstruction of a quadof image cells from a pair of adjacent rows and a pair of adjacentcolumns of a source image in accordance with the losslessbidirectional-reconstruction process illustrated in FIG. 14 a;

FIG. 14c illustrates application of the lossless bidirectionalreconstruction process illustrated in FIG. 14a , as applied to the Red(R), Green (G), Blue (B) and transparency (a) image-pixel elements of abidirectionally-compacted image pixel to generate correspondingimage-pixel elements of corresponding quad of image cells from a pair ofadjacent rows and a pair of adjacent columns of a source image;

FIG. 15 illustrates a process for losslessly reconstructing a compactedimage that was compacted in accordance with the process illustrated inFIG. 2, wherein the lossless reconstruction is in accordance withsuccessive applications of the vertical and horizontal reconstructionprocesses illustrated in FIGS. 12a-12c and 13a-13c , respectively;

FIG. 16 illustrates a process for selecting a lead-primary-colorextra-data image component to be used for approximately reconstructing ahigh-definition image;

FIG. 17 illustrates a process for selecting a method for approximatelyreconstructing transparency pixel elements of a high-definition image;

FIG. 18 illustrates a process—called from the process illustrated inFIG. 16—for approximately reconstructing primary-color pixel elements ofa compacted image that was compacted in accordance with the processillustrated in FIG. 2, wherein the approximate reconstruction is inaccordance with successive applications of the vertical and horizontalreconstruction processes illustrated in FIGS. 12a-12c and 13a-13c ,respectively, but using only corresponding extra-data associated withthe red extra-data pixel element data;

FIG. 19 illustrates a process—called from the process illustrated inFIG. 16—for approximately reconstructing primary-color pixel elements ofa compacted image that was compacted in accordance with the processillustrated in FIG. 2, wherein the approximate reconstruction is inaccordance with successive applications of the vertical and horizontalreconstruction processes illustrated in FIGS. 12a-12c and 13a-13c ,respectively, but using only corresponding extra-data associated withthe green extra-data pixel element data;

FIG. 20 illustrates a process—called from the process illustrated inFIG. 16—for approximately reconstructing primary-color pixel elements ofa compacted image that was compacted in accordance with the processillustrated in FIG. 2, wherein the approximate reconstruction is inaccordance with successive applications of the vertical and horizontalreconstruction processes illustrated in FIGS. 12a-12c and 13a-13c ,respectively, but using only corresponding extra-data associated withthe blue extra-data pixel element data;

FIG. 21 illustrates a process—called from the process illustrated inFIG. 17—for approximately reconstructing transparency pixel elements ofa compacted image that was compacted in accordance with the processillustrated in FIG. 2, wherein the approximate reconstruction is inaccordance with successive applications of the vertical and horizontalreconstruction processes illustrated in FIGS. 12a-12c and 13a-13c ,respectively, but using only corresponding extra-data associated withthe lead-primary-color extra-data pixel element data that had beenidentified by the process illustrated in FIG. 16;

FIG. 22 illustrates a process—associated with the download and displayof high-definition images in accordance with the image processing systemillustrated in FIG. 1—for approximately reconstructing a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2, wherein the approximate reconstruction isin accordance with successive applications of the vertical andhorizontal reconstruction processes illustrated in FIGS. 12a-12c and13a-13c , respectively, but using only corresponding extra-dataassociated with the lead-primary-color extra-data pixel element datathat had been identified by the process illustrated in FIG. 16, andusing the method for approximately reconstructing transparency pixelelements that had been identified by the process illustrated in FIG. 17;

FIG. 23 illustrates a hybrid process—associated with the download anddisplay of high-definition images in accordance with the imageprocessing system illustrated in FIG. 1, following the processillustrated in FIG. 22—comprising a hybrid of the processes illustratedin FIGS. 15 and 22 for approximately reconstructing, but with higherfidelity than from the process illustrated in FIG. 22, a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2;

FIG. 24 illustrates a hybrid process—associated with the download anddisplay of high-definition images in accordance with the imageprocessing system illustrated in FIG. 1, following the processillustrated in FIG. 23—comprising a hybrid of the processes illustratedin FIGS. 15 and 23 for approximately reconstructing, but with higherfidelity than from the process illustrated in FIG. 23, a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2;

FIG. 25 illustrates a hybrid process—associated with the download anddisplay of high-definition images in accordance with the imageprocessing system illustrated in FIG. 1, following the processillustrated in FIG. 24—comprising a hybrid of the processes illustratedin FIGS. 15 and 24 for approximately reconstructing, but with higherfidelity than from the process illustrated in FIG. 24, a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2;

FIG. 26 illustrates a hybrid process—associated with the download anddisplay of high-definition images in accordance with the imageprocessing system illustrated in FIG. 1, following the processillustrated in FIG. 25—comprising a hybrid of the processes illustratedin FIGS. 15 and 25 for approximately reconstructing, but with higherfidelity than from the process illustrated in FIG. 25, a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2;

FIG. 27 illustrates a hybrid process—associated with the download anddisplay of high-definition images in accordance with the imageprocessing system illustrated in FIG. 1, following the processillustrated in FIG. 26—comprising a hybrid of the processes illustratedin FIGS. 15 and 26 for approximately reconstructing, but with higherfidelity than from the process illustrated in FIG. 26, a high-definitionimage from a compacted image that was compacted in accordance with theprocess illustrated in FIG. 2;

FIG. 28 illustrates a process—associated with the download and displayof high-definition images in accordance with the image processing systemillustrated in FIG. 1, following the process illustrated in FIG.27—comprising a hybrid of the processes illustrated in FIGS. 15 and 26for losslessly reconstructing a high-definition image from a compactedimage that was compacted in accordance with the process illustrated inFIG. 2;

FIG. 29 illustrates the process of FIG. 22 as applied to thereconstruction of a high-definition image from a compacted imageinvolving only a single level of horizontal and vertical compaction;

FIG. 30 illustrates a combination of the processes of FIGS. 27 and 28 asapplied to the reconstruction of a high-definition image from acompacted image involving only a single level of horizontal and verticalcompaction, which provides for a substantially lossless reconstructionof the high-definition image;

FIG. 31 illustrates an alternative progressive image generation processthat provides for generating a base image and a series of differenceimages from a high-definition image, and that provides for transmittingthose images to a client, wherein the difference images are relative toa scaled version of the base image, and the difference images include atleast difference images associated with an associated lead-primary-colorcomponent.

FIG. 32 illustrates an example of a high-definition image used toillustrate the processes illustrated in FIGS. 31 and 38;

FIG. 33 illustrates a scaled image that is generated from a base imageassociated with the high-definition image of FIG. 32, which includes anassociated subset of image pixels defining the base image;

FIG. 34 illustrates a difference image generated as the differencebetween the high-definition image illustrated in FIG. 32 and the scaledimage illustrated in FIG. 33;

FIG. 35 illustrates the base image associated with the imagesillustrated in FIGS. 32-34;

FIG. 36 illustrates a base subset of difference-image pixels of thedifference image illustrated in FIG. 34;

FIG. 37 illustrates a first subset of non-base difference-image pixelsof the difference image illustrated in FIG. 34;

FIG. 38 illustrates a second subset of non-base difference-image pixelsof the difference image illustrated in FIG. 34;

FIG. 39 illustrates an alternative progressive image reconstructionprocess that is a counterpart to the alternative progressive imagingprocess illustrated in FIG. 31, wherein the counterpart process providesfor receiving and displaying the base image, internally generating theassociated scaled image, and then receiving at least the lead-colorcomponents of the difference images to provide for reconstructing atleast an approximation of the high definition image by inversedifferencing the scaled image using the difference image components;

FIG. 40 illustrates a portion of an image including a first portion thatis being displayed on a display in accordance with the processillustrated in FIG. 22-28, 29-30, or 39 of reconstructing ahigh-definition image from a compacted image that had been compacted inaccordance with the process illustrated in FIG. 2, and remainingsurrounding portions that are sequentially processed in accordance withthe process illustrated in FIG. 22-28, 29-30, or 39, for a display thatis not being panned by the user viewing the display;

FIG. 41 illustrates a portion of an image including a first portion thatis being displayed on a display in accordance with the processillustrated in FIG. 22-28, 29-30, or 39 of reconstructing ahigh-definition image from a compacted image that had been compacted inaccordance with the process illustrated in FIG. 2, and remainingportions that are sequentially processed in accordance with the processillustrated in FIG. 22-28, 29-30, or 39, for a display that is beingpanned by the user viewing the display, wherein the remaining portionsof the image are selected responsive to the direction in which thedisplay is being panned; and

FIG. 42 illustrates a portion of an image including a first portion thatis being displayed on a display in accordance with the processillustrated in FIG. 22-28, 29-30, or 39 of reconstructing ahigh-definition image from a compacted image that had been compacted inaccordance with the process illustrated in FIG. 2, and remainingportions that are surrounded by the first portion and that aresequentially processed in accordance with the process illustrated inFIG. 22-28, 29-30, or 39, for a display that is being zoomed by the userviewing the display, wherein the remaining portions of the image are ofsuccessively higher resolution than the first portion of the image.

DESCRIPTION OF EMBODIMENT(S)

Referring to FIG. 1, an image processing system 10 provides foruploading a high-definition image 12 from a website proprietor 14, andsequentially compacting this into a losslessly-reconstructable set ofimage components 16 that can be readily transmitted from an internetserver 18 to an associated internet client 20 at the request of a user22 of an associated internet website 24 who wishes to display thehigh-definition image 12 on a display 26 of an internet-connected device28. For example, in one set of embodiments, the high-definition image 12is converted to losslessly-reconstructable form 16 by an imageprocessing application 30 running either as a separate internet-basedimage server 32, on a computing device 34 of the website proprietor 14,or on the internet server 18.

The high-definition image 12 comprises a Cartesian array of M rows by Ncolumns of pixels 36, wherein each pixel 36 comprises a pixel element R,G, B for each of the primary colors, red R, green G, and blue B, andpossibly a pixel element α for transparency α, i.e. a total of fourpixel elements R, G, B, α, each of which for example, comprises anN_(P)-bit unsigned integer that can range in value from 0 to γ. Forexample, in one set of embodiments, N_(P)=8, so that γ=255. Accordingly,the high-definition image 12, with four pixel elements R, G, B, α perpixel 36, comprises a total of N×M×4 pixel elements R, G, B, α, whichfor a large high-definition image 12 can require an unacceptably longperiod of time (from the standpoint of the user 22) to fully transmit ifotherwise transmitted in original form directly over the internet 38from the internet website 24 hosted by the internet server 18, to theinternet-connected device 28 of the user 22 for presentation on thedisplay 26 associated therewith.

For example, the internet-connected device 28 of the user 22 maycomprise either a desktop or laptop personal computer (P.C.), a tabletdevice, a smart phone device, or a user-wearable device such asinternet-connected eyewear, a virtual-reality display or awrist-connected device, any of which might support functionality toprovide for either panning or zooming images, either of which can poseadditional demands on associated bandwidth for image transmission ordisplay. Furthermore, internet websites are presently automaticallyranked based at least in part on the speed at which associated webpagesand associated images are displayed. Limitations in transmissionbandwidth force digital images to be delivered either slowly withlossless compression to preserve quality or much more quickly with acompromise in that quality due to more lossy compression approaches.Historically, internet applications have almost universally adoptedlossy compression approaches for delivering more complex, non-graphicalimages such as digital photographs because the delays of losslessapproaches are unacceptable to most internet users and limitations indevice displays often could not present the advantages of losslesscompression anyway. However, as device displays increase in both pixelquantity and quality, and as user expectations for better imagesincrease, especially as zooming in on images becomes an increasinglycommon practice, there is a greater demand for increased perceived imagequality as long as there is not a significant perceived compromise indelivery and presentation speed.

Accordingly, there exists a need to provide the user 22 with perceivedhigh-quality images at a perceived speed that is acceptably fast—or atleast not unacceptably slow—culminating with a display of an essentiallylossless reconstruction 12′ of the original high-definition image 12,thereby confirming the perception of the high quality of the displayedimage. To this end, the losslessly-reconstructable set of imagecomponents 16 includes a base image IMG^(P,P) generated as a result of Pstages of compaction in each of the horizontal (row) and vertical(column) directions of the original high-definition image 12, whereineach stage of compaction—for example, two to one compaction in anexemplary embodiment—completed in both directions results in a reductionin the number of pixel elements R, G, B, α by a factor of 4 in theexemplary embodiment. More particularly, in the superscript “P, P”, thefirst “P” indicates the level of horizontal compaction of rows of thehigh-definition image 12, and the second “P” indicates the level ofvertical compaction of columns of the high-definition image 12, wherein,following each level of compaction, the corresponding number of rows orcolumns in the resulting compacted image is half the correspondingnumber of rows or columns in the source image subject to that level ofcompaction. In the exemplary embodiment, each level of compactionreduces the corresponding number of rows or columns by half, with agiven level of bidirectional compaction reducing the number of pixels 36to 25% of the corresponding number of pixels 36 in the source imagesubject to that level of compaction. Accordingly, the total number ofpixels 36 in the base image IMG^(P,P) is less than the correspondingnumber of pixels 36 in the high-definition image 12 by a factor of1/(4^(P)); for example, 1/256 for P=4 levels of compaction.

The losslessly-reconstructable set of image components 16 furtherincludes a parameter β and a series of extra-data images ED—both ofwhich are described more fully hereinbelow—that provide forsubstantially losslessly reconstructing the original high-definitionimage 12, i.e. a lossless reconstruction 12′ that might differ from theoriginal high-definition image 12 as a result of either truncationerrors in the associated reconstruction calculations, or a the result ofthe effects of data compression or other artifacts that are introducedby the process of transmitting the losslessly-reconstructable set ofimage components 16 over the internet 38 from the internet server 18 tothe internet client 20. The extra-data images ED, in cooperation withparameter β for some of the intermediate images, provide forsuccessively reconstructing and displaying a series of intermediatereconstructed images with successively-improving quality and resolution,culminating with a display of the ultimate lossless reconstruction 12′of the high-definition image 12. Although the total number of pixelelements R, G, B, α in the losslessly-reconstructable set of imagecomponents 16 is the same as in the original high-definition image 12,the former are structured so as to provide for quickly displaying thebase image IMG^(P,P)—thereby conveying the nature of the contentthereof, —and then successively improving the quality of the displayedimage, so as to thereby accommodate the link speed of the internet 38without adversely affecting the perceived speed at which the image isdisplayed and the perceived quality thereof.

For example, referring to FIGS. 2, 3 a-b and 4 a-b, in one set ofembodiments, in accordance with an associated image compaction process200, the extra-data images ED, ED^(1,0), ED^(1,1), ED^(2,1), ED^(2,2), .. . , ED^(P,P−1), ED^(P,P) and base image IMG^(P,P) are generated as aresult of P levels of successive horizontal and vertical compactions ofthe original high-definition image 12, IMG^(0,0) and subsequent,successively-generated compacted intermediate images IMG^(1,0),IMG^(1,1), IMG^(2,1), IMG^(2,2), . . . , IMG^(P,P−1), finally leading tothe generation of the base image IMG^(P,P), which is stored, along withthe extra-data images ED, ED^(1,0), ED^(1,1), ED^(2,1), ED^(2,2), . . ., ED^(P,P−1), ED^(P,P), in the associated losslessly-reconstructable setof image components 16. More particularly, a first intermediate,compacted image IMG^(1,0) and a corresponding first extra-data imageED^(1,0) are first generated by a horizontal compaction process 300, CH{} illustrated in FIGS. 3a-b . More particularly, FIG. 3a illustrates theequations used to compact a given pair of pixel element valuesPV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k)+1, j^(l)) of corresponding pixelelements R, G, B, α of a pair of vertically-adjacent pixels 36 in rowsi^(k) and i^(k)+1 and column j^(l) of the corresponding source image 40,wherein for this first compaction process the source image 40 is theoriginal, uncompacted high-definition image 12 for which k=0 and l=0.For example, FIG. 5 illustrates an example of a M⁰=16×N⁰=16 sourceimage, with the rows indexed by row index i⁰, and the columns indexed bycolumn index j⁰. The superscript “0” for each of these indices and thetotal numbers of rows M⁰ and columns N⁰ is indicative of thecorresponding compaction level of 0. A horizontal compaction reduces thenumber of rows M¹=8 in the resulting first intermediate, compacted imageIMG^(1,0) to half the number of rows M⁰ of the corresponding sourceimage 40, i.e. the high-definition image 12, with the rows of the firstintermediate, compacted image IMG^(1,0) then indexed by a correspondingrow index i¹ that ranges in value from 1 to M¹. For horizontalcompaction, generally the relationship of the row indices i^(k), i^(k+1)of the source 40, IMG^(k,l) and compacted IMG^(k+1,l) images,respectively, is given by i^(k+1)=(i^(k+1))/2. Accordingly, thehorizontal compaction of the pair of pixel element valuesPV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k)+1, j^(l)) from the source image40 results in a single pixel element value PV^(k+1,l)(i^(k+1), j^(l)) inthe resulting compacted image IMG^(k+1,l) and a corresponding extra-dataimage pixel element value ED^(k+1,l)(i^(k+1), j^(l)) in thecorresponding extra-data image ED^(k+1,l). For example, FIGS. 6a and 6brespectively illustrate the first intermediate, compacted imageIMG^(1,0) and the first extra-data image ED^(1,0) resulting from thehorizontal compaction of the high-definition image 12, IMG^(0,0)illustrated in FIG. 5.

Following the horizontal compaction of the original high-definitionimage 12 to generate the first intermediate, compacted image IMG^(1,0)and associated first extra-data image ED^(1,0), the first intermediate,compacted image IMG^(1,0)—used as a source image 40—is verticallycompacted by a vertical compaction process 400, CV{ } illustrated inFIGS. 4a-b to generate a corresponding second intermediate, compactedimage IMG^(1,1) and a corresponding second extra-data image ED^(1,1).More particularly, FIG. 4a illustrates the equations used to compact agiven pair of horizontally-adjacent pixel element values PV^(k,l)(i^(k),j^(l)), PV^(k,l)(i^(k), j^(l)+1) of corresponding pixel elements R, G,B, α of a pair of horizontally-adjacent pixels 36 in columns j^(l) andj^(l)+1 and row i^(k) of the corresponding source image 40. Accordingly,the vertical compaction of the pair of pixel element valuesPV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k), j^(l)+1) from the source image40 results in a single compacted pixel element value PV^(k,l+1)(i^(k),j^(l+1)) in the resulting compacted image IMG^(k,l+1) and acorresponding extra-data image pixel element value ED^(k,l+1)(i^(k),j^(l+1)) in the corresponding extra-data image ED^(k,l+1). For example,FIGS. 7a and 7b respectively illustrate the second intermediate,compacted image IMG^(1,1) and the second extra-data image ED^(1,1)resulting from the vertical compaction of the first intermediate,compacted image IMG^(1,0) illustrated in FIG. 6 a.

Referring to FIGS. 8a-b and 9a-b , alternatively, both the horizontal anvertical compactions can be accomplished with a simultaneousbidirectional compaction by a bidirectional compaction process 800, CB{} illustrated in FIGS. 8a-b , in accordance with the equationsillustrated in FIG. 8a for a quad of pixel element valuesPV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k), j^(l)+1), PV^(k,l)(i^(k)+1,j^(l)), PV^(k,l)(i^(k)+1, j^(l)+1) illustrated in FIG. 8b , so as toprovide for generating a single corresponding compacted pixel elementvalue PV^(k+1,l+1)(i^(k+1), j^(l+1)) in combination with threecorresponding associated extra-data image pixel element valuesED^(k+1,l+1,1)(i^(k+1), j^(l+1)), ED^(k+1,l+1,2)(i^(k+1), j^(l+1)),ED^(k+1,l+1,3)(i^(k+1), j^(l+1)), wherein FIG. 9a illustrates theassociated intermediate, compacted image IMG^(1,1) generated directlyfrom the high-definition image 12, IMG^(0,0) using the equationsillustrated in FIG. 8a , and FIG. 9b illustrates the correspondingassociated extra-data image ED^(1,1) resulting from this bidirectionalcompaction process.

Returning to FIG. 2, following the vertical compaction process 400 togenerate the second intermediate, compacted image IMG^(1,1), the secondintermediate, compacted image IMG^(1,1)—as a source image 40—is thencompacted using the horizontal compaction process 300 to generate athird intermediate, compacted image IMG^(2,1) and a corresponding thirdextra-data image ED^(2,1), respective examples of which are illustratedin FIGS. 10a and 10b , respectively. The third intermediate, compactedimage IMG^(2,1)—as a source image 40—is then compacted using thevertical compaction process 400 to generate a fourth intermediate,compacted image IMG^(2,2) and a corresponding fourth extra-data imageED^(2,2), respective examples of which are illustrated in FIGS. 11a and1b , respectively. The compaction process continues with successivealternations of horizontal and vertical compaction until the finalapplication of the vertical compaction process 400 to generate the baseimage IMG^(P,P) and the corresponding last extra-data image ED^(P,P),

Referring to FIGS. 12a-b , a lossless vertical reconstruction process1200, RV{ } provides for losslessly reconstructing adjacent pixelelement values PV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k), j^(l)+1) from acorresponding compacted pixel element value PV^(k,l+1)(i^(k), j^(l+1))using the corresponding associated extra-data image pixel element valueED^(k,l+1)(i^(k), j^(l+1)), both of which were generated by the verticalcompaction process 400 of FIGS. 4a and 4b , wherein FIG. 12c illustratesthe application of the equations of the lossless vertical reconstructionprocess 1200 illustrated in FIG. 12a to each of the associated pixelelements R, G, B, α, i.e. X=R, G, B, or α.

Referring to FIGS. 13a-b , a lossless horizontal reconstruction process1300, RH{ } provides for losslessly reconstructing adjacent pixelelement values PV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k)+1, j^(l)) from acorresponding compacted pixel element value PV^(k+1,l)(i^(k+1), j^(l))using the corresponding associated extra-data image pixel element valueED^(k+1,l)(i^(k+1), j^(l)), both of which were generated by thehorizontal compaction process 300 of FIGS. 3a and 3b , wherein FIG. 13cillustrates the application of the equations of the lossless horizontalreconstruction process 1300 illustrated in FIG. 13a to each of theassociated pixel elements R, G, B, α, i.e. X=R, G, B, or α.

Referring to FIGS. 14a-b , a lossless bidirectional reconstructionprocess 1400, RB{ } provides for losslessly reconstructing a quad ofpixel element values PV^(k,l)(i^(k), j^(l)), PV^(k,l)(i^(k), j^(l)+1),PV^(k,l)(i^(k)+1, j^(l)), PV^(k,l)(i^(k)+1, j^(l)+1) from acorresponding compacted pixel element value PV^(k+1,l+1)(i^(k+1),j^(l+1)) using the corresponding associated extra-data image pixelelement values ED^(k+1,l+1,1)(i^(k+1), j^(l+1)), ED^(k+1,l+1,2)(i^(k+1),j^(l+1)), ED^(k+1,l+1,3)(i^(k+1), j^(l+1)), all of which were generatedby the bidirectional compaction process 300 of FIGS. 8a and 8b , whereinFIG. 14c illustrates the application of the equations of the losslessbidirectional reconstruction process 1400 illustrated in FIG. 14a toeach of the associated pixel elements R, G, B, α, i.e. X=R, G, B, or α.

Referring to FIG. 15, a first aspect of an image reconstruction process1500 provides for a substantially lossless reconstruction 12′, IMG^(0,0)of the high-definition image 12, IMG^(0,0), beginning, in step (1502),with application of the lossless vertical reconstruction process 1200 tothe base image IMG^(P,P) to generate a first intermediate reconstructedimage IMG^(P,P−1), and then, in step (1504), application of the losslesshorizontal reconstruction process 1300 to the first intermediatereconstructed image IMG^(P,P−1) to generate a second intermediatereconstructed image IMG^(P−1,P−1), continuing with successivealternating applications, in steps (1506) through (1512), of thelossless vertical 1200 and horizontal 1300 reconstruction processes toeach previously-generated intermediate reconstructed image that is usedas a source image 40 to the subsequent lossless reconstruction process,wherein each lossless reconstruction process, horizontal or vertical, isa counterpart to the corresponding compaction process, horizontal orvertical, that had been used to generate the associated compacted imageand associated extra-data image that is being reconstructed. Theextra-data images ED^(P,P), ED^(P,P−1), . . . , ED^(2,2), ED^(2,1),ED^(1,1), ED^(1,0) are the same as those generated during the associatedimage compaction process 200 illustrated in FIG. 2.

Each pixel of the extra-data images ED^(P,P), ED^(P,P−1), . . . ,ED^(2,2), ED^(2,1), ED^(1,1), ED^(1,0) includes associated extra-dataimage pixel values for each of the associated pixel components R, G, B,α. Although this complete set of extra-data image pixel values for eachof the associated pixel components R, G, B, α provides for thesubstantially lossless reconstruction 12′, IMG′^(0,0) of thehigh-definition image 12, IMG^(0,0), it has been found that areconstruction of the high-definition image 12, IMG^(0,0) using only oneof the primary-color pixel components R, G, B from the associatedextra-data images ED^(P,P), ED^(P,P−1), . . . , ED^(2,2), ED^(2,1),ED^(1,1), ED^(1,0) for reconstruction of all primary-color components R,G, B provides for an approximate reconstruction of the high-definitionimage 12, IMG^(0,0) that has sufficiently-high fidelity to be used as anintermediate reconstructed image, which can be made available fordisplay more quickly that can the substantially lossless reconstruction12′, IMG′^(0,0) of the high-definition image 12, IMG^(0,0), because theapproximate reconstruction of the high-definition image 12, IMG^(0,0) isdependent upon only one of the primary-color pixel components R, G, B,which requires only 25% of the extra-data as would be used for alossless reconstruction 12′, IMG′^(0,0). Furthermore, it has been foundthat the fidelity of the approximate reconstruction of thehigh-definition image 12, IMG^(0,0) can be dependent upon which of theprimary-color pixel components R, G, B is selected for the approximatereconstruction, wherein the primary-color pixel component R, G, B thatprovides for the highest-fidelity approximate reconstruction is referredto as the lead-primary-color pixel component X, wherein X is one of R, Gand B.

Referring to FIG. 16, the lead-primary-color pixel component X isidentified by a lead-primary-color identification process 1600.Beginning with step (1602), for a high-definition image 12 having atleast two primary-color components, in step (1604), each of the pixelcomponents R, G, B, α, of the associated pixel element data for each ofthe corresponding pixel elements R, G, B, α is compacted in accordancewith the above-described image compaction process 200 to generate thebase image IMG^(P,P) and the associated extra-data images ED^(P,P),ED^(P,P−1), . . . , ED^(2,2), ED^(2,1), ED^(1,1), ED^(1,0) of thelosslessly-reconstructable set of image components 16. Then, in step(1606), for each primary-color pixel component R, G, B, thecorresponding primary-color pixel component R, G, B of the extra-dataimages ED^(P,P), ED^(P,P−1), . . . , ED^(2,2), ED^(2,1), ED^(1,1),ED^(1,0) is used exclusively to reconstruct an approximate image, i.e. atest image, containing all of the primary-color pixel components R, G, Bfrom the base image IMG^(P,P) and the associated intermediate imagesIMG^(P,P−1), . . . , IMG^(2,2), IMG^(2,1), IMG^(1,1), IMG^(1,0), butusing corresponding extra-data images ED^(P,P), ED^(P,P−1), . . . ,ED^(2,2), ED^(2,1), ED^(1,1), ED^(1,0) of only the corresponding one ofthe primary-color pixel components R, G, B. More particularly, referringto FIG. 18, an R-approximate image IMG(R′)^(0,0) is generated by ared-approximate image reconstruction process 1800, which is the same asthe image reconstruction process 1500 illustrated in FIG. 15, exceptthat only the red-image component is used from the extra-data imagesED_(R) ^(P,P), ED_(R) ^(P,P−1), . . . , ED_(R) ^(2,2), ED_(R) ^(2,1),ED_(R) ^(1,1), ED_(R) ^(1,0) to reconstruct each of the correspondingpixel elements R, G, B, α from the base image IMG^(P,P) and each of theassociated intermediate images IMG^(P,P−1), . . . , IMG^(2,2),IMG^(2,1), IMG^(1,1), IMG^(1,0), i.e. for each of the associatedprimary-color pixel components R, G, B and for the associatedtransparency α component, regardless or color or transparency.Furthermore, referring to FIG. 19, a G-approximate image IMG(G′)^(0,0)is generated by a green-approximate image reconstruction process 1900,which is the same as the image reconstruction process 1500 illustratedin FIG. 15, except that only the green-image component is used from theextra-data images ED_(G) ^(P,P), ED_(G) ^(P,P−1), . . . , ED_(G) ^(2,2),ED_(G) ^(2,1), ED_(G) ^(1,1), ED_(G) ^(1,0) to reconstruct each of thecorresponding pixel elements R, G, B, α from the base image IMG^(P,P)and each of the associated intermediate images IMG^(P,P−1), . . . ,IMG^(2,2), IMG^(2,1), IMG^(1,1), IMG^(1,0), i.e. for each of theassociated primary-color pixel components R, G, B and for the associatedtransparency α component, regardless or color or transparency. Yetfurther, referring to FIG. 20, a B-approximate image IMG(B′)^(0,0) isgenerated by a blue-approximate image reconstruction process 2000, whichis the same as the image reconstruction process 1500 illustrated in FIG.15, except that only the blue-image component is used from theextra-data images ED_(B) ^(P,P), ED_(B) ^(P,P−1), . . . , ED_(B) ^(2,2),ED_(B) ^(2,1), ED_(B) ^(1,1), ED_(B) ^(1,0) to reconstruct each of thecorresponding pixel elements R, G, B, α from the base image IMG^(P,P)and each of the associated intermediate images IMG^(P,P−1), . . . ,IMG^(2,2), IMG^(2,1), IMG^(1,1), IMG^(1,0), i.e. for each of theassociated primary-color pixel components R, G, B and for the associatedtransparency α component, regardless or color or transparency. Then,returning to FIG. 16, in step (1608), each resulting approximatereconstructed image, i.e. separately, each of the R-approximate imageIMG(R′)^(0,0), the G-approximate image IMG(G′)^(0,0), and theB-approximate image IMG(B′)^(0,0), is compared with the losslessreconstruction 12′, IMG′^(0,0) that was based upon the complete set ofextra-data image elements for each of the pixel components R, G, B, α.More particularly, a sum-of-squared difference SSD_(R), SSD_(G),SSD_(B)—between the lossless reconstruction 12′, IMG′^(0,0) and therespective R-approximate image IMG(R)′^(0,0), G-approximate imageIMG(G)′^(0,0) and B-approximate image IMG(B)′^(0,0), respectively—iscalculated as sum of the square of the difference between the values ofcorresponding pixel elements R, G, B, α for each pixel elements R, G, B,α and for all pixels 36 of the respective images, i.e. IMG′^(0,0) andIMG(R)′^(0,0), IMG(G)′^(0,0) or IMG(B)′^(0,0). Based upon comparisons inat least one of steps (1610) and (1612), in one of steps (1514) through(1618), the primary-color pixel component R, G, B associated with thesmallest-valued sum-of-squared difference SSD_(R), SSD_(G), SSD_(B) isthen identified as the lead-primary-color pixel component X, and, instep (1620), the corresponding extra-data images ED_(X) ^(P,P), ED_(X)^(P,P−1), . . . , ED_(X) ^(2,2), ED_(X) ^(2,1), ED_(X) ^(1,1), ED_(X)^(1,0) are saved, as are the extra-data images ED_(Y) ^(P,P), ED_(Y)^(P,P−1), . . . , ED_(Y) ^(2,2), ED_(Y) ^(2,1), ED_(Y) ^(1,1), ED_(Y)^(1,0) and ED_(Z) ^(P,P), ED_(Z) ^(P,P−1), . . . , ED_(Z) ^(2,2), ED_(Z)^(2,1), ED_(Z) ^(1,1), ED_(Z) ^(1,0) for the remaining primary-colorpixel components R, G, B. Accordingly if X=R, then {Y,Z}={G, B}; if X=G,then {Y,Z}={R, B}; and if X=B, then {Y,Z}={R, G}.

Referring to FIG. 17, following the identification of thelead-primary-color pixel component X by the lead-primary-coloridentification process 1600, from step (1622) thereof, atransparency-approximation-method-identification process 1700 is used toidentify a method of approximating the transparency pixel element α whenapproximating the high-definition image 12 prior to receiving thecomplete set of extra-data images ED for the Y, Z and α pixelcomponents. More particularly, in step (1702), the transparencycomponent α of the base image IMG_(α) ^(P,P) is scaled or interpolatedfrom that of the base image IMG_(α) ^(P,P) to generate ascaled/interpolated image IMG_(α_Interp) containing the same number ofpixels—i.e. N×M—as the high-definition image 12, and in one-to-onecorrespondence therewith. Then, in step (1704), referring to FIG. 21, anX-approximate image IMG_(α)(X)′^(0,0) is generated by an X-approximateimage reconstruction process 2100, which is the same as the imagereconstruction process 1500 illustrated in FIG. 15, except that only theX-image component is used from the extra-data images ED_(X) ^(P,P),ED_(X) ^(P,P−1), . . . , ED_(X) ^(2,2), ED_(X) ^(2,1), ED_(X) ^(1,1),ED_(X) ^(1,0) to reconstruct the transparency pixel element α from thebase image IMG_(α) ^(P,P) and each of the associated intermediate imagesIMG_(α) ^(P,P−1), . . . , IMG_(α) ^(2,2), IMG_(α) ^(2,1), IMG_(α)^(1,1), IMG_(α) ^(1,0) Then, in step (1706), the sum-of-squareddifference SSD_(α_Interp) between the transparency α of the losslessreconstruction 12′, IMG_(α)′^(0,0) and the scaled/interpolated imageIMG_(α_Interp) is calculated, as is the sum-of-squared differenceSSD_(X) between the transparency α of the lossless reconstruction 12′,IMG_(α′) ^(0,0) and the X-approximate image IMG_(α)(X)′^(0,0). If, instep (1708), the sum-of-squared difference SSD_(X) based on theX-approximate image IMG_(α)(X)′^(0,0) is less than the sum-of-squareddifference SSD_(α_Interp) based on the scaled/interpolated imageIMG_(α_Interp), then, in step (1710), a parameter β is set to cause theextra-data images ED_(X) ^(P,P), ED_(X) ^(P,P−1), . . . , ED_(X) ^(2,2),ED_(X) ^(2,1), ED_(X) ^(1,1), ED_(X) ^(1,0) to be used to reconstructapproximate images of the transparency pixel elements a when theassociated extra-data images ED_(α) ^(P,P), ED_(α) ^(P,P−1), . . . ,ED_(α) ^(2,2), ED_(α) ^(2,1), ED_(α) ^(1,1), ED_(α) ^(1,0) are notavailable for an associated lossless reconstruction. Otherwise, fromstep (1708), the parameter β is set so as to cause the associatedtransparency pixel elements a to be scaled or interpolated when theassociated extra-data images ED_(α) ^(P,P), ED_(α) ^(P,P−1), . . . ,ED_(α) ^(2,2), ED_(α) ^(2,1), ED_(α) ^(1,1), ED_(α) ^(1,0) are notavailable for an associated lossless reconstruction. Following steps(1708) or (1710), in step (1714), the parameter β is stored for futureuse. The resulting associated approximate extra-data transparency imagesED_(β) ^(P,P), ED_(β) ^(P,P−1), . . . , ED_(β) ^(2,2), ED_(β) ^(2,1),ED_(β) ^(1,1), ED_(β) ^(1,0)—whether approximated as the extra-dataimages ED_(X) ^(P,P), ED_(X) ^(P,P−1), . . . , ED_(X) ^(2,2), ED_(X)^(2,1), ED_(X) ^(1,1), ED_(X) ^(1,0); or scaled or interpolated from thebase transparency image IMG_(α) ^(P,P)—are then used as describedhereinbelow during the associated below-described reconstructionprocess.

Referring to FIGS. 22-28, following the identification by thelead-primary-color identification process 1600 of the lead-primary-colorpixel component X, and the identification by thetransparency-approximation-method-identification process 1700 of themethod of approximating the transparency pixel element α, thelosslessly-reconstructable set of image components 16 can betransmitted—in order of reconstruction—from the internet server 18 tothe internet client 20 upon demand by the internet-connected device 28under control of the user 22, and subsequently progressively displayedon the display 26 of the internet-connected device 28 as the variouslosslessly-reconstructable set of image components 16 are received.Referring to FIG. 22, in accordance with a first approximate imagereconstruction process 2200, after initially receiving and displayingthe base image IMG^(P,P) in step (2202), following receipt of eachextra-data images ED_(X) ^(P,P), ED_(X) ^(P,P−1), . . . , ED_(X) ^(2,2),ED_(X) ^(2,1), ED_(X) ^(1,1), ED_(X) ^(1,0) for the lead-primary-colorpixel component X, an X-approximate high-definition image (IMG_(X′)^(0,0), IMG_(Y′) ^(0,0), IMG_(Z′) ^(0,0)) is generated for each of theprimary-color pixel components R, G, B, and for the transparencycomponent α, using the lead-primary-color pixel component X of thecorresponding extra-data images ED_(X) ^(P,P), ED_(X) ^(P,P−1), . . . ,ED_(X) ^(2,2), ED_(X) ^(2,1), ED_(X) ^(1,1), ED_(X) ^(1,0) alone toprogressively reconstruct the corresponding primary-color images(IMG_(X′) ^(P,P−1), IMG_(Y′) ^(P,P−1), . . . , IMG_(Z′) ^(P,P−1)), . . ., (IMG_(X′) ^(2,2), IMG_(Y′) ^(2,2), IMG_(Z′) ^(2,2)), (IMG_(X′) ^(2,1),IMG_(Y′) ^(2,1), IMG_(Z′) ^(2,1)), (IMG_(X′) ^(1,1), IMG_(Y′) ^(1,1),IMG_(Z′) ^(1,1)), (IMG_(X′) ^(1,0), IMG_(Y′) ^(1,0), IMG_(Z′) ^(1,0)),and (IMG_(X′) ^(0,0), IMG_(Y′) ^(0,0), IMG_(Z′) ^(0,0)), and toreconstruct the transparency component α—i.e. the approximate extra-datatransparency images ED_(β) ^(P,P), ED_(β) ^(P,P−1), . . . , ED_(β)^(2,2), ED_(β) ^(2,1), ED_(β) ^(1,1), ED_(β) ^(1,0)—in accordance withthe transparency-approximation method identified by parameter β, whereinthe resulting primary-color images IMG_(X′) ^(P,P−1), . . . , IMG_(X′)^(2,2), IMG_(X′) ^(2,1), IMG_(X′) ^(1,1), IMG_(X′) ^(1,0), IMG_(X′)^(0,0) associated with the lead-primary-color pixel component X—havingbeen losslessly reconstructed except for the effect of differencesbetween the approximate extra-data transparency images ED_(β) ^(P,P),ED_(β) ^(P,P−1), . . . , ED_(β) ^(2,2), ED_(β) ^(2,1), ED_(β) ^(1,1),ED_(β) ^(1,0) and the corresponding actual extra-data transparencyimages ED_(α) ^(P,P), ED_(α) ^(P,P−1), . . . , ED_(α) ^(2,2), ED_(α)^(2,1), ED_(α) ^(1,1), ED_(α) ^(1,0)—are saved for subsequent imagereconstruction. More particularly, in step (2204), the lossless verticalreconstruction process 1200 is applied to the base image IMG^(P,P) togenerate a first X-approximate intermediate reconstructed image(IMG_(X′) ^(P,P−1), IMG_(Y′) ^(P,P) IMG_(Z′) ^(P,P−1)) using thecorresponding associated approximate extra-data transparency imageED_(β) ^(P,P). If the actual extra-data transparency images ED_(α)^(P,P), ED_(α) ^(P,P−1), . . . , ED_(α) ^(2,2), ED_(α) ^(2,1), ED_(α)^(1,1), ED_(α) ^(1,0) will not later be available during the subsequentreconstruction processes 2300-2800, then the X-component of the firstX-approximate intermediate reconstructed image IMG_(X′) ^(P,P−1)—whichneed not be further refined to account for the effect of transparencyα—is saved for later use in the second approximate image reconstructionprocess 2300 described hereinbelow. Then, in step (2206), the losslesshorizontal reconstruction process 1300 is applied to the firstX-approximate intermediate reconstructed image (IMG_(X′) ^(P,P−1),IMG_(Y′) ^(P,P−1), IMG_(Z′) ^(P,P−1)) to generate a second X-approximateintermediate reconstructed image (IMG_(X′) ^(P−1,P−1), IMG_(Y′)^(P−1,P−1), IMG_(Z′) ^(P−1,P−1)) using the corresponding associatedapproximate extra-data transparency image ED_(β) ^(P,P−1), wherein theX-component IMG_(X′) ^(P−1,P−1) of the second X-approximate intermediatereconstructed image (IMG_(X′) ^(P−1,P−1), IMG_(Y′) ^(P−1,P−1), IMG_(Z′)^(P−1,P−1)) is saved for later use in the second 2300 and third 2400approximate image reconstruction processes. The first approximate imagereconstruction process 2200 continues with alternate applications of thelossless vertical 1200 and horizontal 1300 reconstruction processes onthe most-recently generated X-approximate intermediate reconstructedimage (IMG_(X′), IMG_(Y′), IMG_(Z′)), for example, ultimately in steps(2208), (2210), (2212) and (2214) acting on corresponding associatedX-approximate intermediate reconstructed images (IMG_(X′) ^(2,2),IMG_(Y′) ^(2,2), IMG_(Z′) ^(2,2)), (IMG_(X′) ^(2,1), IMG_(Y′) ^(2,1),IMG_(Z′) ^(2,1)), (IMG_(X′) ^(1,1), IMG_(Y′) ^(1,1), IMG_(Z′) ^(1,1)),(IMG_(X′) ^(1,0), IMG_(Y′) ^(1,0), IMG_(Z′) ^(1,0)), using correspondingassociated approximate extra-data transparency images ED_(β) ^(2,2),ED_(β) ^(2,1), ED_(β) ^(1,1), ED_(β) ^(1,0), so as to provide forultimately reconstructing the final X-approximate intermediatereconstructed image (IMG_(X′) ^(0,0), IMG_(Y′) ^(0,0), IMG_(Z′) ^(0,0)).

Then, referring to FIGS. 23-28, as the subsequent extra-data imagesED_(Y) ^(P,P), ED_(Y) ^(P,P−1), . . . , ED_(Y) ^(2,2), ED_(Y) ^(2,1),ED_(Y) ^(1,1), ED_(Y) ^(1,0) and ED_(Z) ^(P,P), ED_(Z) ^(P,P−1), . . . ,ED_(Z) ^(2,2), ED_(Z) ^(2,1), ED_(Z) ^(1,1), ED_(Z) ^(1,0) are receivedfor the remaining primary-color pixel components Y,Z, and if, and if soas, the extra-data images ED_(α) ^(P,P), ED_(α) ^(P,P−1), . . . , ED_(α)^(2,2), ED_(α) ^(2,1), ED_(α) ^(1,1), ED_(α) ^(1,0) are received for thetransparency component α, then the remaining transparency imagecomponents (IMG_(α) ^(P,P−1), IMG_(Y) ^(P,P−1), IMG_(Z) ^(P,P−1)), . . ., (IMG_(α) ^(2,2), IMG_(Y) ^(2,2), IMG_(Z) ^(2,2)), (IMG_(α) ^(2,1),IMG_(Y) ^(2,1), IMG_(Z) ^(2,1)), (IMG_(α) ^(1,1), IMG_(Y) ^(1,1),IMG_(Z) ^(1,1)), (IMG_(α) ^(1,0), IMG_(Y) ^(1,0), IMG_(Z) ^(1,0)), and(IMG_(α) ^(0,0), IMG_(Y) ^(0,0), IMG_(Z) ^(0,0)) are progressivelyreplaced with corresponding losslessly-reconstructed image componentsand saved as needed for continual improvement of the reconstructedimage, until, as illustrated in FIG. 28, the lossless reconstruction12′, IMG′^(0,0) is ultimately generated an displayed. If thetransparency image components (IMG_(α) ^(P,P), IMG_(Y) ^(P,P), IMG_(Z)^(P,P)), (IMG_(α) ^(P,P−1), IMG_(Y) ^(P,P−1), IMG_(Z) ^(P,P−1)), . . . ,(IMG_(α) ^(2,2), IMG_(Y) ^(2,2), IMG_(Z) ^(2,2)), (IMG_(α) ^(2,1),IMG_(Y) ^(2,1), IMG_(Z) ^(2,1)), (IMG_(α) ^(1,1), IMG_(Y) ^(1,1),IMG_(Z) ^(1,1)), (IMG_(α) ^(1,0), IMG_(Y) ^(1,0), IMG_(Z) ^(1,0)), and(IMG_(α) ^(0,0), IMG_(Y) ^(0,0), IMG_(Z) ^(0,0)) are available toreplace the approximate extra-data transparency images ED_(β) ^(P,P),ED_(β) ^(P,P−1), . . . , ED_(β) ^(2,2), ED_(β) ^(2,1), ED_(β) ^(1,1),ED_(β) ^(1,0), then the X-components of the primary-color intermediateimages (IMG_(X′) ^(P,P−1)), . . . , (IMG_(X′) ^(2,2)), (IMG_(X′)^(2,1)), (IMG_(X′) ^(1,1)), (IMG_(X′) ^(1,0)) will need to beregenerated, because the transparency component α affects each of theprimary-color pixel components R, G, B.

More particularly, following reconstruction of the X-approximatehigh-definition image (IMG_(X) ^(0,0), IMG_(Y′) ^(0,0), IMG_(Z′)^(0,0)), —and if the transparency image components (IMG_(α) ^(P,P),IMG_(Y) ^(P,P), IMG_(Z) ^(P,P)), (IMG_(α) ^(P,P−1), IMG_(Y) ^(P,P−1),IMG_(Z) ^(P,P−1)), . . . , (IMG_(α) ^(2,2), IMG_(Y) ^(2,2), IMG_(Z)^(2,2)), (IMG_(α) ^(2,1), IMG_(Y) ^(2,1), IMG_(Z) ^(2,1)), (IMG_(α)^(1,1), IMG_(Y) ^(1,1), IMG_(Z) ^(1,1)), (IMG_(α) ^(1,0), IMG_(Y)^(1,0), IMG_(Z) ^(1,0)), and (IMG_(α) ^(0,0), IMG_(Y) ^(0,0), IMG_(Z)^(0,0)) are not available, the exact reconstruction of the X-componentIMG_(X) ^(0,0) of the high-definition image 12, —at the end of the firstapproximate reconstruction process 2200, referring to FIG. 23, inaccordance with a second approximate image reconstruction process 2300,following receipt of the extra-data images ED_(Y) ^(P,P), ED_(Z) ^(P,P),and, if available, extra-data transparency image ED_(α) ^(P,P), theimage components IMG_(Y) ^(P,P−1), IMG_(Z) ^(P,P−1)—and image componentIMG_(X) ^(P,P−1) if the transparency image component IMG_(α) ^(P,P) isavailable—are reconstructed exactly from the base image IMG^(P,P) by thelossless vertical reconstruction process 1200, using the correspondingassociated extra-data images ED_(Y) ^(P,P), ED_(Z) ^(P,P) ED_(α/β)^(P,P), after which the exactly-reconstructed image components IMG_(Y)^(P,P−1), IMG_(Z) ^(P,P−1) are saved. Then, the remaining steps of thesecond approximate image reconstruction process 2300—the same as for thefirst approximate image reconstruction process 2200—are applied to thereconstruction of the remaining approximate image components IMG_(Y′)^(k,l), IMG_(Z′) ^(k), for primary color components Y and Z. If thefirst transparency image component IMG_(α) ^(P,P) is available, then, instep (2204), then the X-component IMG_(X) ^(P,P−1) of the associatedintermediate image is regenerated responsive thereto.

Following reconstruction of the X-approximate high-definition image(IMG_(X) ^(0,0), IMG_(Y′) ^(0,0), IMG_(Z′) ^(0,0)) by the secondapproximate image reconstruction process 2300, referring to FIG. 24, inaccordance with a third approximate image reconstruction process 2400,following receipt of the next set of remaining extra-data images ED_(Y)^(P,P−1), ED_(Z) ^(P,P−2), and, if available, extra-data transparencyimage ED_(α) ^(P,P−1), the image components IMG_(Y) ^(P−1,P−1), IMG_(Z)^(P−1,P−1)—and image component IMG_(X) ^(P−1,P−1) if the transparencyimage component IMG_(α) ^(P,P−1) is available—are reconstructed exactlyfrom the image components IMG_(Y) ^(P,P−1), IMG_(Z) ^(P,P−1) saved fromthe second approximate image reconstruction process 2300, by thelossless horizontal reconstruction process 1300 using the correspondingassociated extra-data images ED_(Y) ^(P,P−1), ED_(Z) ^(P,P−2) ED_(α/β)^(P,P−1), after which the exactly-reconstructed image components IMG_(Y)^(P−1,P−1), IMG_(Z) ^(P−1,P−1) are saved. Then, the remaining steps ofthe second approximate image reconstruction process 2300—the same as forthe first 2200 and second 2300 approximate image reconstructionprocesses—are applied to the reconstruction of the remaining approximateimage components IMG_(Y′) ^(k,l), IMG_(Z′) ^(k,l) for primary colorcomponents Y and Z. If the second transparency image component IMG_(α)^(P,P−1) is available, then, in step (2206), then the X-componentIMG_(X) ^(P−1,P−1) of the associated intermediate image is regeneratedresponsive thereto.

The processes of vertical and horizontal reconstruction are successivelyrepeated, —in each case with receipt of the next set of remainingextra-data images ED_(Y) ^(k,l), ED_(Z) ^(k,l) ED_(α) ^(k,l), followedby reconstruction commencing with the highest-resolutionpreviously-saved exactly-reconstructed image components IMG_(Y) ^(k,l),IMG_(Z) ^(k,l) for primary color components Y and Z, —so as to providefor exact reconstruction of the next image components IMG_(Y) ^(k+1,l),IMG_(Z) ^(k+1,l) or IMG_(Y) ^(k,l+1), IMG_(Z) ^(k,l+1).

Eventually, referring to FIG. 25, in accordance with a fourthapproximate image reconstruction process 2500, following receipt of thethird next-to-last set of remaining extra-data images ED_(Y) ^(2,2),ED_(Z) ^(2,2) ED_(α/β) ^(2,2), the image components IMG_(Y) ^(2,1),IMG_(Z) ^(2,1) are reconstructed exactly by vertical reconstruction fromthe image components IMG_(Y) ^(2,2), IMG_(Z) ^(2,2) saved from themost-recent horizontal reconstruction, using the correspondingassociated extra-data images ED_(Y) ^(2,2), ED_(Z) ^(2,2) ED_(α/β)^(2,2), after which the exactly-reconstructed image components IMG_(Y)^(2,1), IMG_(Z) ^(2,1) are saved. Then, the remaining steps of thefourth approximate image reconstruction process 2500—the same as for theprevious approximate image reconstruction processes 2200, 2300, 2400—areapplied to the reconstruction of the remaining approximate imagecomponents IMG_(Y′) ^(k,l), IMG_(Z′) ^(k,l) for primary color componentsY and Z. If the associated transparency image component IMG_(α) ^(2,2)is available, then, in step (2208), then the corresponding X-componentIMG_(X) ^(2,1) of the associated intermediate image is regeneratedresponsive thereto.

Then, referring to FIG. 26, in accordance with a fifth approximate imagereconstruction process 2600, following receipt of the secondnext-to-last set of remaining extra-data images ED_(Y) ^(2,1), ED_(Z)^(2,1) ED_(α/β) ^(2,1), the image components IMG_(Y) ^(1,1), IMG_(Z)^(1,1) are reconstructed exactly by horizontal reconstruction from theimage components IMG_(Y) ^(2,1), IMG_(Z) ^(2,1) saved from the fourthapproximate image reconstruction process 2500, using the correspondingassociated extra-data images ED_(Y) ^(2,1), ED_(Z) ^(2,1) ED_(α/β)^(2,1), after which the exactly-reconstructed image components IMG_(Y)^(1,1), IMG_(Z) ^(1,1) are saved. Then, the remaining steps of the fifthapproximate image reconstruction process 2600—the same as for theprevious approximate image reconstruction processes 2200, 2300, 2400,2500—are applied to the reconstruction of the remaining approximateimage components IMG_(Y′) ^(k,l), IMG_(Z′) ^(k,l) for primary colorcomponents Y and Z. If the associated transparency image componentIMG_(α) ^(2,1) is available, then, in step (2210), then thecorresponding X-component IMG_(X) ^(1,1) of the associated intermediateimage is regenerated responsive thereto.

Then, referring to FIG. 27, in accordance with a sixth approximate imagereconstruction process 2700, following receipt of the next-to-last setof remaining extra-data images ED_(Y) ^(1,1), ED_(Z) ^(1,1) ED_(α/β)^(1,1), the image components IMG_(Y) ^(1,0), IMG_(Z) ^(1,0) arereconstructed exactly by vertical reconstruction from the imagecomponents IMG_(Y) ^(1,1), IMG_(Z) ^(1,1) saved from the fifthapproximate image reconstruction process 2600, using the correspondingassociated extra-data images ED_(Y) ^(1,1), ED_(Z) ^(1,1) ED_(α/β)^(1,1), after which the exactly-reconstructed image components IMG_(Y)^(1,9), IMG_(Z) ^(1,0) are saved. Then, the remaining step of the sixthapproximate image reconstruction process 2700—the same as for theprevious approximate image reconstruction processes 2200, 2300, 2400,2500, 2600—are applied to the reconstruction of the remainingapproximate image component IMG_(Y′) ⁰, IMG_(Z′) ⁰ for primary colorcomponents Y and Z. If the associated transparency image componentIMG_(α) ^(1,1) is available, then, in step (2212), then thecorresponding X-component IMG_(X) ^(1,0) of the associated intermediateimage is regenerated responsive thereto.

Finally, referring to FIG. 28, in accordance with a final imagereconstruction process 2800, following receipt of the last set ofremaining extra-data images ED_(Y) ^(1,0), ED_(Z) ^(1,0) ED_(α/β)^(1,0), the remaining final reconstructed high-definition imagecomponents IMG_(Y) ^(0,0), IMG_(Z) ^(0,0) are reconstructed exactly byhorizontal reconstruction from the image components IMG_(Y) ^(1,0),IMG_(Z) ^(1,0) saved from the sixth approximate image reconstructionprocess 2700, using the corresponding associated extra-data imagesED_(Y) ^(1,0), ED_(Z) ^(1,0) ED_(α/β) ^(1,0), after which theexactly-reconstructed image components IMG_(Y) ^(0,0), IMG_(Z) ^(0,0)are displayed or saved. If the associated transparency image componentIMG_(α) ^(1,0) is available, then, in step (2214), the correspondingX-component IMG_(X) ^(0,0) of the associated high-definition image isregenerated responsive thereto.

It should be understood that the number of iterations of associatedlossless vertical 1200 and horizontal 1300 reconstruction processeswithin the approximate image reconstruction processes 2200, 2300, 2400,2500, 2600, 2700, 2800—i.e. the number of progressions in the associatedprogressive image—is not limiting, and that each of the associatedreconstructed intermediate images need not necessarily be displayed onthe display 26, but one or more of the intermediate images could insteadbe saved in memory for future display or processing. Furthermore, theassociated storage of one or more associated intermediate images may betransitory, for example, only for a sufficiently long duration to enablea subsequent reconstruction of an associated relatively higherresolution image component. For example, one or more of therelatively-lowest resolution intermediate images might not be displayed,but could be used to reconstruct associated one or morerelatively-higher resolution images, one or more of which are displayed.Intermediate images that are not needed—after the display thereof isrefreshed with the display of a different image—for subsequentlyreconstructing a relatively-higher resolution image, need not be saved.

For example, referring to FIG. 29, a single-level X-approximate imagereconstruction process 2900 commences in step (2902) with receipt of anassociated base image IMG^(1,1). Then, in step (2904), following receiptof an associated first lead-primary-color component extra-data imageED_(X) ^(1,1) and an associated approximate extra-data transparencyimage ED_(β) ^(1,1), the base image IMG^(1,1) is transformed to acorresponding first X-approximate intermediate image {IMG_(X′) ^(1,9),IMG_(Y′) ^(1,9), IMG_(Z′) ^(1,0)} by application of the associatedlossless vertical reconstruction process 1200. Then, in step (2906),following receipt of an associated second lead-primary-color componentextra-data image ED_(X) ^(1,0), and an associated approximate extra-datatransparency image ED_(β) ^(1,0), the first X-approximate intermediateimage {IMG_(X′) ^(1,9), IMG_(Y′) ^(1,9), IMG_(Z′) ^(1,0)} is transformedto the resulting X-approximate high-definition image {IMG_(X′) ^(0,9),IMG_(Y′) ^(0,9), IMG_(Z′) ^(0,0)} by application of the associatedlossless horizontal reconstruction process 1300.

Then, referring to FIG. 30, a single-level high-definition imagereconstruction process 3000 commences in step (3002) with receipt of theassociated base image IMG^(1,1)—the same as received in step (2902) andused in the single-level X-approximate image reconstruction process2900. Then, in step (3004), following receipt of the associated firstset of extra-data images ED_(X) ^(1,1), ED_(Y) ^(1,1), ED_(Z) ^(1,1),ED_(α) ^(1,1) for each of the primary-color pixel components X, Y, Z andfor the transparency component α (i.e. the remaining extra-data imagesED_(Y) ^(1,1), ED_(Z) ^(1,1), ED_(α) ^(1,1) that had not already beenreceived), the base image IMG^(1,1) is transformed to a correspondingfirst intermediate image {IMG_(X) ^(1,9), IMG_(Y) ^(1,9), IMG_(Z)^(1,0)} by application of an associated lossless vertical reconstructionprocess 1200. Then, in step (3006), following receipt of an associatedsecond set of extra-data images ED_(X) ^(1,0), ED_(Y) ^(1,0), ED_(Z)^(1,0), ED_(α) ^(1,0) for each of the primary-color pixel components X,Y, Z and for the transparency component α (i.e. the remaining extra-dataimages ED_(Y) ^(1,0), ED_(Z) ^(1,0), ED_(α) ^(1,0) that had not alreadybeen received), the first intermediate image {IMG_(X) ^(1,9), IMG_(Y)^(1,9), IMG_(Z) ^(1,0)} is transformed to the resulting high-definitionimage {IMG_(X) ^(0,9), IMG_(Y) ^(0,9), IMG_(Z) ^(0,0)} by application ofthe associated lossless horizontal reconstruction process 1300.

It should be understood that the order in which the complete set oflosslessly-reconstructed pixel elements R, G, B, α are generated is notlimiting. For example, this could be strictly in order of increasingimage resolution (i.e. increasing total number of pixels 36); in orderof pixel element R, G, B, α, for example, completing all resolutions ofeach primary-color pixel component X, Y, Z before continuing with thenext, followed by all resolutions of the transparency component α; or ahybrid thereof.

Furthermore, the relative ordering of horizontal and verticalcompaction, and resulting vertical and horizontal reconstruction, couldbe reversed, with the high-definition image 12 being initiallyvertically compacted rather than initially horizontally compacted.

The image processing system 10 is not limited to the illustrated 2:1compaction ratio of rows or columns in the source image 40 tocorresponding rows or columns in the compacted image. For example, theteachings of the instant application could also be applied incooperation with the image processing systems disclosed in U.S. Pat.Nos. 8,855,195 and 8,798,136, each of which are incorporated herein byreference, wherein, in summary, an original, high-resolution image issequentially compacted on a server device through a number of lowerresolution levels or representations of the same image to a finallow-resolution image, hereinafter referred to as the base image, whilewith each such compaction to a lower resolution image, extra-data valuesare also generated and thereafter stored with the base image on theserver device so that, when later losslessly sent to a receiving device,the base image and extra-data values can be processed by the receivingdevice through reconstruction algorithms to losslessly reconstruct eachsequentially higher resolution representation and to ultimately restorethe original image, subject to minor truncation errors. This previousimage transmission algorithm is applied independently to all colorchannels or components comprising the original high-resolution imagesuch as, for example, primary colors of red, green, blue and as well asan alpha (transparency) component if present, so that the extra-datavalues are effectively generated and stored on the server device and,upon later demand, sent by the server device to the receiving device asextra-data images comprised of extra-data pixels, each pixel comprisedof values for the same number of color components as the original image,and which together with all extra-data images from each level ofcompaction form a single set of extra-data images supporting thesequential reconstruction by the receiving device of progressivelyhigher resolution images from the base to final image.

As another illustrative example, an original image having resolution ofM₀ horizontal by N₀ vertical pixels—wherein, for convenience. M₀ and N₀are evenly divisible by eight, with each image pixel having four colorcomponent values including red, green, blue and an alpha or transparencychannel, each value having a minimum possible value of 0 and a maximumpossible value of 255, —is sequentially compacted on a server device toprogressively lower resolutions of half the previous resolution, threetimes in each direction, first horizontally then vertically each time,resulting in a base image resolution comprised of M₀/8 horizontal byN₀/8 vertical pixels, and an extra-data image for each of the six totalcompactions, with each of the base image and the extra-data imagescomprising pixels having values for all four components, i.e. R, G, B,and a, of the original image. Each such compaction to half resolution ina given direction is accomplished by calculating each Lower ResolutionPixel Value, LRPV, for each component of the lower resolution image asthe average value of the corresponding, sequential pair of HigherResolution Pixel Values, HRPV₁ and HRPV₂ in the prior higher resolutionimage that are adjacent in that direction.LRPV=(HRPV₁+HRPV₂)/2  (1)

Each such operation on HRPV₁ and HRPV₂ is also accompanied by thecalculation of a corresponding Extra-Data Pixel Value EDPV given byEDPV=(HRPV₁−HRPV₂+255)/2  (2)

Therefore with each compaction in each direction of the relativelyhigher resolution image there is an extra-data pixel value calculatedfor each lower resolution pixel value calculated. Accordingly, theresolution (i.e. horizontal and vertical pixel count) of each extra-dataimage formed is equal to the resolution of the lower resolution imageformed from the compacted higher resolution image. Such extra-dataimages can be treated as single images for purposes of storage and lateruse or they can be combined to abut other extra-data images to formlarger extra-data images for additional efficiency, for example, eachlarger extra-data image including both extra-data images correspondingto the compaction of both directions of each progressively lower imageresolution. In any case, all such extra-data images subsequently form acomplete set of extra-data values for the receiving device tosequentially and progressively reconstruct from the base image in thereverse order of compaction up through each higher resolution until thatof the original image is achieved. In each such reconstruction thecorresponding pair of adjacent, higher resolution pixel values, HRPV₁and HRPV₂, for each component are determined from each lower resolutionpixel value, LRPV, and the corresponding extra-data pixel value, EDPV,through reconstruction derived from the above formulae:HRPV₁=LRPV+EDPV−255/2  (3)HRPV₂=LRPV−EDPV+255/2  (4)

In this particular example, compaction is shown to reduce every twoadjacent pixels of a higher resolution image to one, representing alower resolution image having half the resolution of the higherresolution image in the direction of compaction. Such formulae can bemodified to support a variety of algorithms to achieve a variety ofalternative compactions, such as, but not limited to, four pixels tothree or three pixels to two, depending on the desired resolution of therelatively lower resolution images.

During compaction from each higher resolution image to the next lowerresolution image representation, each pixel value of the extra-dataimage for each color component is fundamentally derived from thedifference of two spatially adjacent pixel values of that colorcomponent from the higher resolution image. In many practical imagingapplications, especially those involving high-resolution photography,the difference between two spatially adjacent pixel values of oneprimary color channel is often substantially similar to the differencebetween those same pixels for the other primary color channels. In fact,when all such extra-data pixel values of all primary colors from typicalphotographic images are displayed as a full color extra-data image, thatimage appears substantially like a grayscale image with only sparselypopulated pixels of visually obvious non-gray values. For this reason,the color palette of extra-data pixel values necessary to represent theextra-data image typically contains significantly fewer colors than thecolor palette of the higher resolution image. Since many losslesscompression algorithms rely on smaller color palettes for theireffectiveness, one advantage of the previously referenced algorithm isthat, when losslessly compressed, the total bandwidth required totransmit the lower resolution base image and the set of extra-dataimages combined is typically less than the bandwidth required totransmit the higher resolution image alone. Assuming the receivingdevice can rapidly execute the reconstruction algorithm, which is almostuniversally the case with today's devices due the simplicity of relatedcomputational operations, the image processing system 10 supports asignificantly faster transmission and presentation of losslesslycompressed images.

The image processing system 10 inherently provides multiple,progressively higher resolution representations of the high-resolutionimage prior to achieving the final original resolution. This allows aserver device such as a web server to first send the base image as arelatively very small file followed by each respective extra-data imagefile so that a receiving and display device such as a web browser canquickly show the base image and then progressively improve the qualityof that image through reconstruction as it receives the extra-data imagefiles rather than waiting for a single high-resolution image file beforeshowing it.

In accordance with the image processing system 10, an original imagecomprising an array of pixel values each having two or more colorcomponents is sequentially compacted—for example, on a server device—toone or more progressively lower resolution representations culminatingin a lowest resolution base image, each such compaction resulting in anaccompanying two dimensional array of extra-data pixels comprisingextra-data values for each color component and therefore forming anextra-data image, with all of the extra-data images together forming acomplete set of extra-data images, whereby the complete set ofextra-data images can be used in a reconstruction process to reconstructthe base image into progressively higher resolution images culminatingwith the original image.

In accordance with one aspect of the image processing system 10 and anassociated set of embodiments, reconstruction is then applied—forexample, on the server device—to each of the primary color components ofthe base image to reconstruct a primary color test image of the sameresolution as the original high-resolution image, but using theextra-data image pixel values of only that single primary color as asubstitute for all extra-data image primary colors for that particulartest image, and thereby, having done so for each single primary color,creating an intermediate test image for each. The pixel values of eachprimary color test image are then compared to all primary color pixelvalues of the original high-resolution image to determine which testimage results in the best approximation of that originalhigh-resolution.

Such best approximation can be based on any comparative process as wouldoccur to one skilled in the art, including but not limited to asummation of the results of the least squared error between all pixelvalues of each primary color of the original and test image. Thatprimary color component of the extra-data images resulting in the bestapproximation is referred to herein as the lead primary-color pixelcomponent X.

The complete set of extra-data images can be divided into two subsets ofextra-data images, wherein a first subset includes all the pixel valuesof the complete set for just the lead-primary-color pixel component Xand a second subset that includes the pixel values of only the remainingprimary-color pixel components Y,Z, the two subsets together effectivelyproviding all pixel values of the complete set, and the two subsetsthereafter stored on the server device with the base image which itselfalso includes a value indicating the lead primary color in its metadata.

If the original image—and therefore also the second subset of extra-dataimages—includes a non-primary color component to be treated as an alphachannel, then the server device further uses reconstruction of thecomponent of the base image to reconstruct a first high-resolution testimage using the first set of extra-data images. The server also createsa second high-resolution test image by simply scaling up the alphachannel of the base image to the same resolution as the original imageusing conventional scaling algorithms. Both such test images are thencompared to the alpha channel component of the original high-resolutionimage to determine which method offers the best approximation inaccordance with the same method used to determine the lead primarycolor. An indication to use either alpha channel scaling orreconstruction of the alpha channel with the first extra-data subset asa best approximation is then stored as an additional value in themetadata of the base image.

In further accordance with the image processing system 10, upon demandfrom a receiving device, the server sends the base image with itsmetadata (or uses an alternate means of communicating the lead primarycolor and method for alpha channel treatment) followed by the firstsubset of extra-data images comprising pixel values of the lead primarycolor, and thereafter, the server device sends the second subset ofextra-data images for the remaining color components. While sequentiallyreceiving the first subset of extra-data images, the receiving deviceapplies reconstruction, through algorithms resident on the receivingdevice, or provided to the receiving device by the server device, forexample, through the Hypertext Markup Language of a web page, toprogressively reconstruct an intermediate image having the resolution ofthe original high-resolution image from the base image and the pixelvalues of the first subset of extra-data images, and using such pixelvalues as an estimate for all other extra-data primary color components.If an alpha or transparency component is also present on the receivingdevice, the receiving device, as instructed by the metadata of the baseimage, either scales that component up to the final resolution, or usesthe first subset of extra-data image values for reconstruction as well.Since the base image includes all colors of the original high-resolutionimage, this process therefore creates an intermediate image with thefull color and resolution of the original image, albeit with less thanfull fidelity due to the use of a single primary color of the extra-dataimages during reconstruction. Thereafter, and upon receiving the secondsubset set of extra-data images, the receiving device then performsprogressive reconstruction using the base image and the pixel values ofthe remaining extra-data image components of the second subset,replacing the final image pixel values for the remaining primary colorcomponents and alpha channel (if present) with the reconstructed valueswhen complete, and thereby fully and losslessly restoring the originalimage.

The intermediate image—i.e. the X-approximate high-definition image(IMG_(X) ^(0,0), IMG_(Y′)′^(0,0), IMG_(Z′) ^(0,0))—created by the imageprocessing system 10 presents the full resolution of the finalhigh-definition image 12 in much less time than required to directlydisplay the high-definition image 12 because the reconstruction to thatresolution only requires the transmission and reception of a singlecolor component of the extra-data images (i.e. the first subset) insteadof all color components of the complete set. While the fidelity of thisintermediate image is very likely to be less than that of the finalimage, it will nonetheless be a very good representation if the pixelvalues of first subset of extra-data images are good estimates of thecorresponding pixel values of all other primary colors. As mentionedhereinabove, compaction of typical images shows that extra-data imageswhose pixel values are primarily based on differences of spatiallyadjacent pixel values of the original image appear substantially asgrayscale images. This implies that values for all primary-color pixelcomponents R, G, B of such extra-data pixels are very similar to oneanother, and therefore that using one primary color value of the extradata is a reasonable estimate for all other primary color values of anextra-data pixel when used for reconstruction. Accordingly, inaccordance with another aspect of the image processing system 10 and anassociated set of embodiments, any of the primary-color pixel componentR, G, B may be used as pixel component X instead of thelead-primary-color pixel component X for generating the X-approximateintermediate and high-definition images—i.e. without the determinationof the lead-primary-color pixel component X by the above-describedlead-primary-color identification process 1600—in the associatedapproximate image reconstruction processes 2200, 2300, 2400, 2500, 2600,2700 so as to provide for losslessly restoring the originalhigh-definition image 12, notwithstanding that a lead-primary-colorpixel component X selected using the above-described lead-primary-coloridentification process 1600 would typically provide for the best qualityassociated intermediate images to be generated by the associatedapproximate image reconstruction processes 2200, 2300, 2400, 2500, 2600,2700.

Notwithstanding that the similarities of extra-data pixels for differentprimary-color pixel components R, G, B, generally justify the use of anyprimary color R, G, B as that estimate, it should be understood that theabove-described lead-primary-color identification process 1600 may beused to determine and select the lead-primary-color pixel component Xthat provides for the highest fidelity approximate reconstruction of theX-approximate high-definition image (IMG_(X) ^(0,0), IMG_(Y′) ^(0,0),IMG_(Z′) ^(0,0)).

In accordance with another aspect, a progressive imaging process firstscales an original image down to relatively-lower resolution usingconventional scaling algorithms to create a base image of smaller filesize for faster transmission. The base image includes each of theassociated color components, and possibly a transparency component.Then, in preparation for later delivery, each color component, and ifavailable, the transparency component, of that relatively-lowerresolution image is then scaled back up to the size of—i.e. the samenumber of pixels as—the original image, for example, by interpolation ofpixel values at pixel locations between the corresponding locations ofthe base image, wherein the resulting upscaled image has lower fidelitythan the original image. Each of the color components, and if available,the transparency component, of the upscaled image is then differencedwith the corresponding components of the original image to generate anassociated extra-data difference image that can be used to reconstructthe original image from the upscaled image.

The base image; information describing the aforementioned process oralgorithm used to upscale the base image to an upscaled image; and theextra-data difference image is then delivered to a client system,wherein the described upscaling process is used to convert the baseimage to an upscaled image. The extra-data difference image is thenapplied to correct each color-component, and if available, thetransparency component, of the up-scaled image using an associatedinverse differencing process—i.e. the inverse of the differencingprocess used to generate the extra-data difference image—to reconstructthe original image. Although the up-scaled image is only anapproximation of the original image, the pixel color-component valuesthereof are sufficiently similar to those of the original image so thatthe associated extra-data difference image appears substantially as agrayscale image (i.e. wherein each of the color-component values of eachpixel of the extra-data difference image are very similar to oneanother). Accordingly, a single color-component of the extra-datadifference image can be used as an estimate for the extra data of othercolors in the extra data difference image, to reconstruct anintermediate image of higher quality than the up-scaled image. Theremaining primary color components of the extra data image can then besubsequently delivered to reconstruct the remaining colors in the finalimage with original fidelity. It should be understood that this approachcan be applied to either lossy or lossless progressive deliverydepending on the process of generating the base and extra data imagesand the degree to which all colors of extra data are applied duringreconstruction.

The relatively-smaller base image can therefore be transmitted rapidlyand then up-scaled by a receiving device to the original resolution,followed by the transmission of the extra-data image which issubsequently used by the receiving device to correct the up-scaled imageusing the inverse differencing process to reconstruct the original imagepixel values.

Generally, this approach of using a single color component of extra datato reconstruct other color components of a relatively-higher fidelityimage can be used in accordance with any imaging method employingdifference data between two pixels with an expectation that the valuesof the associated difference data will be similar for different colorcomponents. Such a differences may be between values of spatiallyadjacent pixels, between original pixels and approximations to thosepixels, and even between a particular pixel value and the value of thatpixel in a future frame of a sequential motion video display of imagesbased on a prediction of where that pixel value is most likely to be ina future frame. For example, such a prediction could suggest the futurepixel value to be in the same image location as the original. However,that location may also be predicted to change to a new location in thefuture frame based on a variety of known motion estimation, predictionand encoding methods.

For example, referring to FIGS. 31-37, an alternative progressive imagegeneration and transmission process 3100—for example, operating on theinternet server 18—commences in step (3102) with receipt of ahigh-definition image 12, i.e. what is also referred to as an originalhigh-definition image 12, O, an example of which is illustrated in FIG.32, comprising a plurality of pixels 36, O(i,j), each of which includesa plurality of primary-color pixel components R, G, B and possibly alsoa transparency component α. In accordance with one set of embodiments,the high-definition image 12 includes a sparse subset of base-imagepixels 36, 36* that provide for representing the high-definition image12, O, but at a relatively lower definition and with relatively-fewerpixels 36 that can be transmitted relatively-more quickly than theentire high-definition image 12, O. This sparse subset of base-imagepixels 36, 36*, O(i,j) can be created from the high-definition image 12,O—associated with corresponding base-image-pixel locations 36′ withinthe high-definition image 12, O, —by any arbitrary method such asdown-sampling through scaling methods—possibly resulting in values ofthe pixel components R, G, B, α that are different from those of thecorresponding original image pixels—or even sampling of the originalimage pixels 36, O(i,j). In step (3104), the base-image pixels 36, 36*,O*(i,j) are selected from the high-definition image 12, O, or otherwisedetermined, so as to define an associated base image 50, O*, forexample, as illustrated in FIG. 35 and described further hereinbelow.Then, referring also to FIG. 33, in step (3106), a corresponding scaledimage 42, S—having same number of pixels as the high-definition image12, O and in one-to-one correspondence therewith—is determined from thevalues and locations 36′ of the base-image pixels 36, 36* in thehigh-definition image 12, O. The scaled image 42, S comprises aplurality of scaled image pixels 44, S(i,j) in combination with theassociated base-image pixels 36, 36*, with each scaled image pixel 44,S(i,j) containing the same components R, G, B, α as the correspondingbase-image pixels 36, 36*, wherein the value of each component R, G, B,α of each scaled image pixel 44, S(i,j) is determined from thecorresponding values of the relatively-proximate associated base-imagepixels 36, 36*, for example, by interpolation, for example, bilinearinterpolation, polynomial interpolation or spline interpolation, whichmay be independent of any scaling method that might be used in step(3104) to determine the associated base-image pixels 36, 36*, O*(i,j) asan alternative to sampling the original image pixels 36, O(i,j), whichaccounts for both the values of the associated components R, G, B, α ofthe base-image pixels 36, 36*, and the locations 36′ of those valueswithin the scaled image 42, S. Then, referring also to FIG. 34, in step(3108), a corresponding difference image 46, D—having same number ofpixels as the high-definition image 12, O and the scaled image 42, S,and in one-to-one correspondence with each—is determined by subtractingthe scaled image 42, S from the high-definition image 12, O. Moreparticular, each difference pixel 48, Dk(i,j) is given by:Dk(i,j){R,G,B,α}=O(i,j){R,G,B,α}−S(i,j){R,G,B,α}  (5)wherein k represents an interleave level that is described hereinbelowand which identifies a corresponding subset of difference pixel 48,Dk(i,j), and each component R, G, B, α is determined separately. If thebase-image pixels 36, 36*, O*(i,j) are sampled from the original imagepixels 36, O(i,j), then the corresponding difference pixels 48, Dk(i,j)will be zero-valued.

Following step (3108) of the alternative progressive image generationand transmission process 3100, referring again to FIG. 35, in step(3110), the base image 50, O* is transmitted to a client, for example,for either display on an associated display 26, or for subsequentprocessing in favor of the display of an associatedrelatively-higher-definition image. Then, in step (3112), a counterk—used to account for corresponding associated sets of difference imagepixels 48, Dk(i,j)—is initialized to a value of zero, and then, in step(3114), the lead-primary-color pixel component X (or more generally,pixel component X which need not be the “best” primary-color) of thek^(th) set of difference image pixels 48, Dk(i,j){X} is transmitted tothe client for use in reconstructing a relatively-higher-fidelity image,i.e. an image that is of higher fidelity than the most-recentlyreconstructed image, wherein the lead-primary-color pixel component X—ifused—is selected as described hereinabove. In one set of embodiments,referring to FIG. 36, for k=0, the 0^(th) set—i.e. a base set—ofdifference image pixels 48, 48.0, D0(i,j) of an associated basedifference image 46.0 correspond to, and provide for correcting, thebase image 50, O*. Furthermore, the subsequent sets of difference imagepixels 48, 48.k, Dk(i,j) of each set k are interleaved and mediallylocated with respect to the previously-transmitted sets k of differenceimage pixels 48, Dk(i,j). Furthermore, referring to FIG. 37, a first setof non-base difference image pixels 48, 48.1, D1(i,j) of an associatedfirst-interleave difference image 46.1, D1 are interleaved and mediallylocated with respect to the base-image pixels 36, 36*, and, referring toFIG. 38, a second set of non-base difference image pixels 48, 48.2,D2(i,j) of an associated second-interleave difference image 46.2, D2 areinterleaved and medially located with respect to both the base-imagepixels 36, 36* and the first set of non-base difference image pixels 48,48.1, D1(i,j). Following step (3114), if, in step (3116), thelead-primary-color pixel components X of the all sets of differenceimage pixels 48, Dk(i,j){X} have not been transmitted to the client,then, in step (3118), the counter k is incremented, and the processrepeats with step (3114).

Otherwise, from step (3116), if the lead-primary-color pixel componentsX of the all sets of difference image pixels 48, Dk(i,j){X} have beentransmitted to the client, and if the client requests to further refinethe reconstruction of the image, then, the above steps (3112) through(3118) are repeated as corresponding steps (3120) through (3126) asdescribed above, but instead of transmitting only the lead-primary-colorpixel components X—or generally, pixel components X—of all sets ofdifference image pixels 48, Dk(i,j){X}, the remaining primary-colorpixel components Y, Z, and if available, the transparency component α,all sets of difference image pixels 48, Dk(i,j){Y,Z, α} are sequentiallytransmitted to the client. Then, following step (3116) if only thelead-primary-color pixel components X—or generally, pixel componentsX—are transmitted, or following step (3124) if all the primary-colorpixel components X, Y, Z are transmitted, in step (3128), thealternative progressive image generation and transmission process 3100returns control to await the next high-definition image 12, O to beprocessed.

Referring to FIG. 39, from the perspective of the internet client 20, inaccordance with an alternative progressive image reconstruction process3900, in step (3902), the base image 50, O* transmitted by step (3110)of the above-described transmission process 3100 is received, and instep (3904), a corresponding scaled image 42, S is generated from thebase image 50, O* using the same methodology as used in step (3106) ofthe above-described generation process 3100. Then, in step (3906), acomposite of the base image 50, O* and the scaled image 42, S—an exampleof which is illustrated in FIG. 33, and which is referred to hereincollectively as the scaled image 42, S—is displayed on the display 26 ofthe internet client 20. Then, in step (3908), a counter k—used toaccount for corresponding associated sets of difference image pixels 48,Dk(i,j)—is initialized to a value of zero, and then, in step (3910), thelead-primary-color pixel component X of the k^(th) set of differenceimage pixels 48, Dk(i,j){X}—as transmitted in step (3114) of theabove-described transmission process 3100—is received, after which instep (3912), for each primary-color pixel components X, Y, Z of eachdifference image pixel 48, Dk(i,j), an approximation of each of thecorresponding original, high-definition image pixels 36, O(i,j) isreconstructed using only the lead-primary-color pixel component X—orgenerally, pixel component X—of the k^(th) set of the correspondingdifference image pixels 48, Dk(i,j){X}, as follows:O(i,j){R,G,B,α}=S(i,j){R,G,B,α}+Dk(ij){X}.  (6)

Following step (3912), if, in step (3914), the lead-primary-color pixelcomponents X—or generally, pixel components X—of the all sets ofdifference image pixels 48, Dk(i,j){X} have not been received andprocessed, then, in step (3916), the counter k is incremented, and theprocess repeats with step (3910).

Otherwise, from step (3914), if the lead-primary-color pixel componentsX of the all sets of difference image pixels 48, Dk(i,j){X} have beenreceived and processed, and if further image refinement is desired, thenthe above steps (3908) through (3916) are repeated as correspondingsteps (3918) through (3926) as described above, but instead of receivingonly the lead-primary-color pixel components X—or generally, pixelcomponents X—of all sets of difference image pixels 48, Dk(i,j){X}, theremaining primary-color pixel components Y, Z, and if available, thetransparency component α, all remaining sets of difference image pixels48, Dk(i,j){Y,Z, α} are sequentially received and processed. Moreparticularly, in step (3922), each of the corresponding original,high-definition image pixels 36, O(i,j) is reconstructed substantiallylosslessly, as follows:O(i,j){R,G,B,α}=S(i,j){R,G,B,α}+Dk(i,j){R,G,B,α}.  (7)

Then, following step (3914) if only the lead-primary-color pixelcomponents X—or generally, pixel components X—are received, or followingstep (3924) if all the primary-color pixel components X, Y, Z arereceived, in step (3928), the alternative progressive imagereconstruction process 3900 returns control to await the next imaged tobe received and processed.

Alternatively, rather than progressively transmitting subsets 46.0,46.1, 46.2 of the difference image 46, D in step (3114) and possiblystep (3122), and receiving those subsets 46.0, 46.1, 46.2 of thedifference image 46, D in step (3910) and possibly step (3920), theentire difference image 46, D may be transmitted as a single block ofdata in step (3114) and possibly step (3122), following transmission ofthe base image 50, O* in step (3110), and received as single block ofdata in step (3910) and possibly step (3920), following the generationof the scaled image 42, S in step (3904).

In accordance with yet another aspect and an associated set ofembodiments, the image processing system 10 could provide for thedelivery of an image that is relatively lossy in comparison with theoriginal image, but at a rate of delivery that is substantially fasterotherwise possible when otherwise transmitted substantiallylosslessly—subject to the precision of the associated mathematicaloperations—restored in accordance with the above-described approximateimage reconstruction processes 2200, 2300, 2400, 2500, 2600, 2700followed by the above-described final image reconstruction process 2800.For example, in accordance with one set of embodiments, an approximate,relatively lossy, intermediate image may be reconstructed by only thefirst approximate image reconstruction process 2200 using only thelead-primary-color pixel component X—or generally, pixel component X—ofextra-data images ED_(X) to reconstruct each of the color components ofthe reconstructed image, wherein the lead-primary-color pixel componentX may be determined in accordance with the above-describedlead-primary-color identification process 1600, or, alternatively asdescribed hereinabove, pixel component X may be selected arbitrarily.Accordingly, the reconstruction of a relatively lossy image using onlythe lead-primary-color pixel component ED_(X)—or generally, pixelcomponent X—precludes the need for receiving and processing theremaining primary-color pixel components ED_(Y,Z), thereby providing fordisplaying the reconstructed final lossy image substantially morequickly than otherwise possible when losslessly reconstructing theoriginal image. Furthermore, the base image IMG^(P,P) and associatedextra-data images ED_(X) ^(P,P), ED_(X) ^(P,P−1), . . . , ED_(X) ^(2,2),ED_(X) ^(2,1), ED_(X) ^(1,1), ED_(X) ^(1,0) created during the imagecompaction process 200 may be further processed using known minimizationand/or compression steps—for example, JPEG compression—to reduce theirfile sizes—and therefore, their associated transmission times,—resulting in faster delivery, but with an inherent further loss ofimage quality in the corresponding resulting reconstructed images.

The similarities amongst different color components of the extra-dataimages cannot necessarily be extended to an alpha or transparencychannel because such a component often has spatial characteristics fardifferent from those of the primary color channels. In fact, in typicalimages, alpha channel content likely has a spatial structure that issmoothly varying (for example, to support gradient blending), andtherefore simple scaling to the higher resolution can be both simple andsufficient for the alpha channel of an intermediate image. In any case,the aforementioned testing on the server device of such scaling comparedto reconstruction of the alpha component using the lead primary colorextra data will provide the best guidance for which method should beused by the receiving device for the intermediate image.

All color components of the extra-data images are still contained in thecombination of the first and second subsets. Such extra-data images aresimply sent as a first subset of essentially grayscale imagesrepresenting the chosen first subset primary color component, forexample, green, while the second subset contains the remaining colorcomponent values, for example, red, blue and alpha. In other words, suchextra-data images fundamentally comprise the same amount of total data,whether sent as the complete, full color image, or as the two subsets ofthe compacted image and associated extra data. Accordingly, from thatperspective, there is no additional bandwidth required by the imageprocessing system 10 to transmit and receive the complete extra-dataimage values relative to transmitting a high-definition image 12 in itsentirety. Assuming the additional reconstruction processing by thereceiving device adds negligible time, the image processing system 10therefore provides for the transmission and display of the final,high-resolution image in substantially the same time as might otherwisebe required to display the high-definition image 12 while also providingfor a high-resolution approximation to that high-definition image insignificantly less time than if the high-definition image 12 wereotherwise directly received and displayed.

From the perspective of the internet server 18, for example, acting asWebserver, the image processing system 10 initially receives andpreprocess a high-definition image 12, i.e. a high-resolution image,having at least two primary color components. The high-definition image12 is progressively decimated in width and height while also creating aset of extra-data images comprising extra-data pixel values for allcolor components or channels, resulting in the creation and storage of alower resolution base image, in such a way that the reverse decimationprocess can be used, beginning with the base image, to losslesslyreconstruct the original high-resolution image. Then, for each primarycolor, reverse decimation is used to reconstruct a high-resolution testimage from the base image, using the extra-data image pixel values forthat primary color, for all primary colors of the test image. Then, theinternet server 18/webserver determines which reconstructed primarycolor test image produces the least total mean squared error between allprimary color pixel values of the test image and those of the originalhigh-resolution image, and indicates this least mean squared error coloras the “lead” color in the base image metadata. Then, a first extra-dataimage subset is created and stored from the extra-data images havingpixel values only for this lead color, and a second extra-data imagesubset is also created and stored from the extra-data images havingpixel values excluding this color, but including all remaining colors ofthe set of extra-data images. If the high-definition image 12 includesan alpha or transparency channel as one of the color channels, theinternet server 18/webserver uses reverse decimation to reconstruct thatchannel of the high-resolution image from the alpha channel of the baseimage using the first extra-data image subset to create a first alphachannel test image, and uses conventional scaling algorithms to scale upthe alpha channel of the base image to the resolution of the originalhigh-resolution image to create a second alpha channel test image. Thenthe internet server 18/webserver determines which of either the firstalpha channel test image or second alpha channel test image produces theleast total mean squared error between such image and the alpha channelof the original high-resolution image, and as a result, indicates theassociated method as a value in the metadata of the base image metadata.Then, upon demand from a receiving device of an internet client 20, i.e.an internet-connected device 28, the internet server 18/webservercommunicates thereto the base image (with metadata) and the firstextra-data image subset followed by the second extra-data image subset,so as to provide for the substantially lossless reconstruction of thehigh-definition image 12.

The present invention may be applied to single images or individually toeach of a mosaic array of smaller area images comprising a larger areaimage according to the visibility of each said smaller image in a givenapplication. For example, a display device may display a particular areaof an image which has been improved with extra resolution data only forthat particular area and possibly it's immediate surround withoutrequiring the download of extra resolution data for remainingnon-displayed areas. As a user interacts with the display device for thepurpose of displaying new areas of the larger image, such as by panning,the extra resolution data for those new areas can then be downloaded toimprove the newly displayed areas.

For example, referring to FIG. 40, a displayed-portion of stationaryimage 12, 52′ is a portion within a larger, but stationary image 12, 52that is received, processed and displayed in accordance with any of theabove-described image reconstruction processes 2200-3000, 3900. Inanticipation of a prospective panning of the displayed-portion ofstationary image 12, 52′ within the stationary image 12, 52, thecorresponding above-described image reconstruction processes 2200-3000,3900 can be applied to reconstruct non-displayed pixels in advance, forexample, in the order of establishing bands of reconstructed pixels thatare concentric with respect to the displayed-portion of stationary image12, 52′, for example, in the order indicated by the number associatedthe illustrated image pixels, i.e. 0 through 3, wherein the pixels ofthe displayed-portion of stationary image 12, 52′ are each indicated as“0”. Referring to FIG. 41, when what had been a stationary image 12, 52undergoes panning, the resulting displayed-portion 12, 54′ of anassociated panned image 12, 54 moves within the panned image 12, 54 inan associated pan direction 56, and in anticipation of this movement,the corresponding above-described image reconstruction processes2200-3000, 3900 can be applied to reconstruct non-displayed pixels inadvance of the movement so as to mitigate against delays associated withnon-displayed pixels that will need to be displayed as thedisplayed-portion 12, 54′ of the panned image 12, 54 moves in the pandirection 56. Accordingly, the order in which the non-displayed pixelsare reconstructed is inversely related to the likely time delay beforethat pixel will likely be displayed, so that the sooner the pixel isexpected to be displayed, the sooner that pixel will be reconstructed inadvance of that display. For example, FIG. 41 illustrates a prospectiveordering of reconstruction based upon the illustrated pan direction 56,with the order indicated by the number associated the illustrated imagepixels, i.e. 0 through 6, wherein the pixels of the displayed-portion12, 54′ of the panned image 12, 54 each indicated as “0”.

Furthermore, as another example, the above-described imagereconstruction processes 2200-3000, 3900 can be applied in advance tonon-displayed pixels that are anticipated to be displayed as a result ofan image-zooming operation. For example, referring to FIG. 42, a zoomedimage 58 is illustrated including a first displayed portion of zoomedimage 58′ that is initially displayed, and associated second 58″ andthird 58′″ prospective displayed portions of the zoomed image 58 thatcould be displayed responsive to the user zooming the display. Followingdisplay of the first displayed portion of zoomed image 58′—with pixelsidentified in FIG. 42 with “0”, the pixels identified in FIG. 42 with“1” are reconstructed in advance using the above-described imagereconstruction processes 2200-3000, 3900 in anticipation of displayingthe second displayed portion of zoomed image 58″, and the pixelsidentified in FIG. 42 with “2” are then reconstructed in advance usingthe above-described image reconstruction processes 2200-3000, 3900 inanticipation of displaying the third displayed portion of zoomed image12, 58′″, wherein each of the first 58′, second 58″ and third 58′″displayed portions each have the same number of pixels in total.

The image processing system 10 therefore provides for the transmissionand display of a high-resolution image by producing an intermediateimage having the same resolution as the final high-resolution image,albeit with lower intermediate fidelity, but in a much faster time thanthe presentation of that final image and with virtually no increase inthe bandwidth required for the delivery and display of that final image.This relatively much faster presentation of this high-resolutionintermediate image therefore significantly accelerates the user'sperception of how fast the image content appears, thereby supporting thetransmission and display of high-resolution images without otherwiseexcessive perceived delay.

While specific embodiments have been described in detail in theforegoing detailed description and illustrated in the accompanyingdrawings, those with ordinary skill in the art will appreciate thatvarious modifications and alternatives to those details could bedeveloped in light of the overall teachings of the disclosure. It shouldbe understood, that any reference herein to the term “or” is intended tomean an “inclusive or” or what is also known as a “logical OR”, whereinwhen used as a logic statement, the expression “A or B” is true ifeither A or B is true, or if both A and B are true, and when used as alist of elements, the expression “A, B or C” is intended to include allcombinations of the elements recited in the expression, for example, anyof the elements selected from the group consisting of A, B, C, (A, B),(A, C), (B, C), and (A, B, C); and so on if additional elements arelisted. Furthermore, it should also be understood that the indefinitearticles “a” or “an”, and the corresponding associated definite articles“the” or “said”, are each intended to mean one or more unless otherwisestated, implied, or physically impossible. Yet further, it should beunderstood that the expressions “at least one of A and B, etc.”, “atleast one of A or B, etc.”, “selected from A and B, etc.” and “selectedfrom A or B, etc.” are each intended to mean either any recited elementindividually or any combination of two or more elements, for example,any of the elements from the group consisting of “A”, “B”, and “A AND Btogether”, etc. Yet further, it should be understood that theexpressions “one of A and B, etc.” and “one of A or B, etc.” are eachintended to mean any of the recited elements individually alone, forexample, either A alone or B alone, etc., but not A AND B together.Furthermore, it should also be understood that unless indicatedotherwise or unless physically impossible, that the above-describedembodiments and aspects can be used in combination with one another andare not mutually exclusive. Accordingly, the particular arrangementsdisclosed are meant to be illustrative only and not limiting as to thescope of the invention, which is to be given the full breadth of theappended claims, and any and all equivalents thereof.

What is claimed is:
 1. A method of processing an image, comprising: a.receiving image data of a relatively-high-resolution image incorporatinga plurality of color components: b. for each color component of saidplurality of color components, successively compacting said image dataof said color component so as to form both a plurality ofsuccessively-lower-resolution images and a corresponding plurality ofsets of extra data, wherein each successively lower-resolution image ofsaid plurality of lower-resolution images, in combination with acorresponding set of extra data, provides for substantially-losslesslyreconstructing a next-higher resolution image of said plurality ofsuccessively-lower-resolution images; c. for each color component ofsaid plurality of color components, forming a corresponding color-testimage by reconstructing each of said color components of saidhigh-resolution image from said plurality ofsuccessively-lower-resolution images in combination with correspondingsets of said extra data associated with only said color component, andreconstructing a component of a color-reference image corresponding tosaid color component from said plurality of lower-resolution images incombination with said corresponding set of said extra data correspondingto said color component; and d. storing a color-component indicator as astored color-component indicator identifying the color component forwhich a corresponding said color-test image is least different from saidcolor-reference image.
 2. A method of processing an image as recited inclaim 1, wherein the operation of successively compacting said imagedata comprises transforming the image data from every pair of adjacentrow pixels of a first image to corresponding image data of a singlecorresponding row pixel of a second image, wherein said first image iseither said relatively-high-resolution image or an image of saidplurality of successively-lower-resolutions images, and said secondimage is a different image of said plurality ofsuccessively-lower-resolutions images.
 3. A method of processing animage as recited in claim 1, wherein the operation of successivelycompacting said image data comprises wherein the operation ofsuccessively compacting said image data comprises transforming the imagedata from every pair of adjacent column pixels of a first image tocorresponding image data of a single corresponding column pixel of asecond image, wherein said first image is either saidrelatively-high-resolution image or an image of said plurality ofsuccessively-lower-resolutions images, and said second image is adifferent image of said plurality of successively-lower-resolutionsimages.
 4. A method of processing an image as recited in claim 1,wherein the operation of successively compacting said image datacomprises wherein the operation of successively compacting said imagedata comprises transforming the image data from a quad of adjacentcolumn and row pixels of a first image to corresponding image data of asingle corresponding pixel of a second image, wherein said first imageis either said relatively-high-resolution image or an image of saidplurality of successively-lower-resolutions images, and said secondimage is a different image of said plurality ofsuccessively-lower-resolutions images.
 5. A method of processing animage as recited in claim 1, wherein the operation of successivelycompacting said image data comprises transforming the image data fromevery pair of adjacent row pixels of a first image to correspondingimage data of a single corresponding row pixel of a second image, andtransforming the image data from every pair of adjacent column pixels ofsaid second image to corresponding image data of a single correspondingcolumn pixel of a third image, wherein said first image is either saidrelatively-high-resolution image or an image of said plurality ofsuccessively-lower-resolutions images, and said second and third imagesare different images of said plurality of successively-lower-resolutionsimages.
 6. A method of processing an image as recited in claim 1,wherein the operation of successively compacting said image datacomprises transforming the image data from every pair of adjacent columnpixels of a first image to corresponding image data of a singlecorresponding column pixel of a second image, and transforming the imagedata from every pair of adjacent row pixels of said second image tocorresponding image data of a single corresponding row pixel of a thirdimage, wherein said first image is either saidrelatively-high-resolution image or an image of said plurality ofsuccessively-lower-resolutions images, and said second and third imagesare different images of said plurality of successively-lower-resolutionsimages.
 7. A method of processing an image as recited in claim 1,wherein said relatively-high-resolution image further incorporates atransparency component, further comprising: a. scaling or interpolatingsaid transparency component of a lowest-resolution image of saidplurality of successively-lower-resolution images to form a firsttransparency-test image in one-to-one pixel correspondence with saidrelatively-high-resolution image; b. forming a second transparency-testimage by reconstructing said transparency components of saidhigh-resolution image from said plurality ofsuccessively-lower-resolution images in combination with correspondingsets of said extra data associated with only said color component saidstored color-component indicator; c. reconstructing atransparency-reference image corresponding to said transparencycomponent from said plurality of lower-resolution images in combinationwith said corresponding set of said extra data corresponding to saidtransparency component; and d. storing a transparency-componentindicator as a stored transparency-component indicator identifying whichof said first or second transparency-test image is least different fromsaid transparency-reference image.
 8. A method of processing an image asrecited in claim 1, further comprising, responsive to receiving arequest from a client device for said relatively-high-resolution image:a. transmitting to said client device all color components of alowest-resolution image of said plurality ofsuccessively-lower-resolution image; and b. in order of increasingresolution, transmitting to said client device only a selected colorcomponent of a corresponding set of said extra data of each of saidplurality corresponding plurality of sets of extra data, wherein saidselected color component corresponds to the color component identifiedby said stored color-component indicator.
 9. A method of processing animage as recited in claim 1, further comprising, following transmissionof each set of said extra data of each of said plurality correspondingplurality of sets of extra data, in order of increasing resolution,transmitting to said client device all remaining components of saidextra data of said plurality corresponding plurality of sets of extradata.
 10. A method of processing an image as recited in claim 8, furthercomprising transmitting to said client device, said storedtransparency-component indicator.
 11. A method of processing an image asrecited in claim 9, further comprising transmitting to said clientdevice, said stored color-component indicator.